Showing posts with label chart matching. Show all posts
Showing posts with label chart matching. Show all posts

Confirmation bias in the Wyman and Vyse experiment

Review of “Science versus the stars: A double-blind test of the validity of the NEO Five-Factor Inventory and computer-generated astrological natal charts” [Download]

This article has been peer reviewed and published by Correlation, 29, No. 2, pp. 26-40. Copyright © 2014 by Kenneth McRitchie. [Download PDF]

Abstract. Psychologists Alyssa Jayne Wyman and Stuart Vyse designed their replication of Shawn Carlson’s double-blind astrological experiment to resolve the problem that the participants could not identify their own California Psychological Inventory profiles any better than their own astrological profiles, as written by reputable astrologers. To simplify these self-identification tasks and ascertain the validity of each of these profile types, the authors used the NEO-FFI psychological self-test versus computer-generated astrological profiles. No astrologers participated. The authors claimed that their test subjects could identify their NEO-FFI profiles at a significant rate but not the astrological profiles. However, a scrutiny of the experimental methodology shows evidence that the claimed findings were due to biases and inefficiencies introduced, perhaps unintentionally, by the authors. The authors’ selective sampling of student subjects, their use and modification of computer-generated astrological profiles, their requirement of a signed astrological knowledge and beliefs questionnaire, the institutionalized bias of their college, and the authority that the authors held over the students all provided opportunities that the authors used to circumvent the double-blind test protocols and sway the results to confirm their own biased beliefs. 

The 2008 experiment by psychologists Alyssa Jayne Wyman and Stuart Vyse (herein referred to as “the authors”) intended to replicate the influential Shawn Carlson double-blind astrological experiment published in Nature (1985). The part of Carlson’s study that most concerned the authors was an inconclusive result that raised questions on the usefulness of self-identification to validate psychological testing. Carlson’s test subjects could not identify their own psychological profiles any better than their astrological profiles (W&V, 288). This result was evidence that neither the astrological nor the psychological tests could be personally validated. 

To resolve this problem, Wyman and Vyse designed an experiment to make personal validation easier but also to study identifications that are falsely personal due to biases. One of these biases is that people generally hold an unrealistically enhanced or positive view of themselves, identified by Taylor and Brown (1988). Another, known as the P.T. Barnum effect, is the tendency for people to accept ambiguous descriptions as being unique to themselves, even though they are generally true for everyone, identified by Forer (1949). Finally, there are biases based on uncritical belief in astrology or in psychology. To prevent their own bias in their experiment, Wyman and Vyse needed to ensure that they did not design test methodologies that would make the self-identification tasks so obvious that they would pose little risk of disconfirming their validation hypotheses.

In his study of mainly University of California student test subjects (N=100+), Carlson claimed that the participating astrologers (N=29) could not accurately match California Psychological Inventory (CPI) profiles to the test subjects’ natal charts any better than would be expected by chance. For this test, the astrologers were given one real and two randomly selected bogus CPIs for each natal chart. They were asked to rate the individual sections of the three CPIs and then rank the three according to what they thought would be the best match to the natal chart.

Similarly, Carlson asked his student test subjects to identify their own astrological profiles that the astrologers had written. Given their real astrological profile and two others randomly selected from the other students, the subjects had to rate the individual sections in each of the three astrological profiles and then rank the three according to what they thought best matched themselves. By using the same procedure, the subjects were also required to identify their own CPI profiles from two others, randomly selected from the other subjects.

In his analysis, Carlson became suspicious of the data from the students’ astrological rating task and discarded it. However, Carlson accepted the data of the students’ ranking task even though it was unusual. That task had a control group whose members were not given their real astrological profiles, yet the control group successfully chose the pre-selected profiles at a significantly low probability against chance (p<0.01, where significance is p<0.05), and the actual test subjects chose their profiles at chance expectancy. Carlson attributed the surprising result for the control group to a “statistical fluctuation.” Carlson also found that the test subjects could not identify their own CPI profiles at a rate better than chance expectancy.

Despite these negative results, the discarded data, and the statistical anomaly, Carlson concluded, “We are now in a position to argue a surprisingly strong case against natal astrology as practiced by reputable astrologers” (Carlson, 425). 

At the time of their own experiment, Wyman and Vyse were unaware that Carlson’s data actually supported astrology. By following up on questions raised by American psychologist Joseph Vidmar (2008), German psychologist Suitbert Ertel (2009) published a reassessment of Carlson’s data. It turned out that Carlson had not followed his hypothesis and his analysis was incorrect. The astrologers had successfully matched the CPI profiles to natal charts at a statistically significant rate in both of their tasks. In consideration of this success, Ertel agreed with Vidmar’s suggestion that the unlikely performance of the control group was suspect. The statistical anomaly weakened Carlson’s claim because of the possibility that the data for the controls and the test subjects might have been switched, perhaps inadvertently.

Hypothesis formation

In an earlier replication of Carlson’s experiment, American psychologists John McGrew and Richard McFall (1990) had argued that both the astrologers and the test subject might have failed to identify the CPIs for the same non-astrological problem. The CPI is a sophisticated test instrument that requires training to interpret. All of Carlson’s participants might have had difficulty in understanding the terms and the graphical scales that the CPI used to describe personality traits (M&M, 76). Although Wyman and Vyse did not cite McGrew and McFall, this was the problem that they wanted to resolve. 

In their own replication, Wyman and Vyse did not try to test the skills of astrologers as Carlson had done, or as McGrew and McFall had done. Instead, they tested whether a very basic psychological test could be personally validated compared to very basic astrological interpretations. They looked for simplicity, ease of execution, replicable methods, and results that would explain differences.

Wyman and Vyse had found several two-choice CPI identification studies, with a choice between one real and one bogus CPI profile, which had been performed after Carlson’s three-choice experiment. These studies had provided some evidence for personal validation of the CPI. The results were in the right direction but less than statistically significant. A two-choice format appeared to be easier for the subjects to discriminate than a three-choice format. (W&V, 288) (1) 

As a further improvement, the authors used the newly-developed NEO Five-Factor Inventory (NEO-FFI) of personality. This questionnaire is based on the Big Five personality theory that assesses five broad domains or dimensions of personality: neuroticism (N), extraversion (E), openness (O), agreeableness (A), and conscientiousness (C). These dimensions are easy to grasp. For example, “I try to be courteous to everyone I meet” contributes to the Agreeableness score and “I like to be where the action is” contributes to the Extraversion score. The authors chose this test because, “The NEO-FFI contains only five dimensions, all of which are easily understood and well embedded in the vernacular language of personality description, whereas the CPI contains 18 dimensions, a number of which may be difficult for many people to evaluate” (W&V 297).

For the psychological part of their experiment, Wyman and Vyse hypothesized that by using the easier NEO-FFI and the two-choice format, their test subjects (N=52) would be able to identify their own personality profiles at a significant rate (W&V, 289). Evidence that supported this hypothesis would confirm the usefulness of the personal identification methodology to validate psychological testing, which the Carlson experiment had failed to do.

For the astrological part of their experiment, Wyman and Vyse asked whether their test subjects could identify their own natal charts by reading computer-generated astrological profiles (herein referred to as CGAPs). Each subject was given their real CGAP and one that was randomly selected from the other test subjects. However, unlike their NEO-FFI strategy, the authors found themselves unable to form a hypothesis for their CGAP strategy. “Because no previous study had used a two-choice test with astrological profiles, we were unable to make a hypothesis in this case” (W&V, 289). Either the authors had failed to research the literature or failed to acknowledge that they were performing a Vernon Clark type experiment. The Vernon Clark experiment (1961) was the first, and for many years the best known, double-blind chart-matching test of astrology. It had used a two-choice format.

Aside from the Vernon Clark oversight, the authors’ argument for their inability to form an astrological hypothesis raises a critical methodological issue. Wyman and Vyse rationalized their test strategy against Karl Popper’s (1963) argument for falsifiable scientific predictions. The purpose of hypothesis testing is not to confirm existing conjectures, theories, or beliefs but to seriously challenge, refute, and falsify them.
“It is easy to obtain confirmation, or verifications, for nearly every theory—if we look for confirmations. Confirmations should count only if they are the result of risky predictions; that is to say, if, unenlightened by the theory in question, we should have expected an event which was incompatible with the theory—an event which would have refuted the theory.” (Popper, 47-48)
Bias leads one to look for strategies that will validate one’s favorite theories. The CPI self-test had proved to be unexpectedly difficult to validate through a self-identification methodology. Wyman and Vyse chose the NEO-FFI self-test specifically because they predicted it would be easier and thus less risky. At the same time, the authors found that they were unable make an astrological hypothesis, which would in fact have been a much riskier prediction because the hypothesized event would be incompatible with current scientific thought. The authors’ claimed inability to form an astrological hypothesis went against Popper’s argument of testing risky and falsifiable conjectures. 

For any scientific evaluation, the default position of statistical inference is the null hypothesis. The null hypothesis holds that there is no relationship between two measured phenomena. In the authors’ test strategy, the measured phenomena were the test subjects’ natal charts and their CGAPs. If the authors’ test results confirmed the astrological null hypothesis it would necessarily disconfirm or falsify the inferred hypothesis of an empirical relationship, at least for the experimental method used. This was the unspoken hypothesis that the authors claimed they were unable to make yet which they were willing to test. If the test results rejected the astrological null hypothesis, then it would give support to this unspoken astrological hypothesis and the associated astrological theory.

Seeing what they were looking for

Falsifiable hypotheses, whether spoken or assumed, are necessary to test scientific conjectures and theory, yet they do not insure against confirmation bias. Psychologist Raymond Nickerson (1998) described confirmation bias as instances where “One selectively gathers, or gives undue weight to, evidence that supports one’s position while neglecting to gather, or discounting, evidence that would tell against it” (Nickerson, 175). Nickerson explains that confirmation bias can take the form of conscious and deliberate case-building, as illustrated by the practices of attorneys and debaters, where the bias is fairly obvious. But in its usual psychological sense, confirmation bias occurs by engaging in case-building unwittingly, without intending or even being aware of biased selectivity in the acquisition and use of evidence. 

A critical review of the experimental methodology used by Wyman and Vyse should determine whether their sample of test subjects was selected to favor their hypothesis, whether external factors were used to influence a favorable result, whether unequal methodologies were applied to the different hypotheses, and whether selective assumptions replaced diligent research in areas of expertise.

If Wyman and Vyse intended to be pragmatic and avoid errors in a subject not familiar to them, their unspoken astrological hypothesis nevertheless rested upon unexamined assumptions. The authors stated, “Astrologers’ natal charts and psychologists’ personality profiles share a common purpose—to provide a description of the respondent’s personality.” They stated that both psychology and astrology provide a “personality assessment” (W&V, 287). This comparison was not as simple and direct as the authors suggested. 

Even among psychologically minded astrologers, distinctions are made between psychological and astrological assessments. American psychiatrist Bernard Rosenblum (1983), who uses and teaches astrology, has argued that each of these two disciplines offers “different vantage points on the prism of the self.” Psychology was developed from a medical model and focuses on healing disturbed states, whereas astrology emphasizes the inner meaning of impediments to freedom, the cyclic patterns of life stages, and the identification of positive potential (Rosenblum, 13).

A consideration of these different vantage points suggests a sort of psychological uncertainty principle regarding the extent of personality information that one could expect to reliably evaluate from a questionnaire compared to the extended period of an individual’s life stages and personal development. Self-test questionnaires like the NEO-FFI or CPI may give a reliable point-in-time snapshot of personality traits but this information is prone to change as the person matures. American psychologists Brent Roberts and Daniel Mroczek (2008) found that personality traits change in adulthood. “In terms of individual differences in personality change, people demonstrate unique patterns of development at all stages of the life course, and these patterns appear to be the result of specific life experiences that pertain to a person’s stage of life” (Roberts & Mroczek, 31).

By contrast, natal chart interpretations, without the snapshot overlay of the current planetary alignments, must be understood as general assessments of personal potential or destiny developed over an entire lifetime. Instead of capturing a moment in time, the reliability of natal chart descriptions must be considered over the longer term. This is why astrologers have argued for testing mature test subjects. Previous double-blind astrological experiments, such as those by Vernon Clark (1961), Neil Marbell (1981), McGrew and McFall (1990), and Michael Shermer (c. 1999) understood the importance of using mature test subjects. Mature individuals have better knowledge of their own potentials and development. (2)

Other differences between psychology and astrology are diversity and context. Although many people, including many astrologers, have tried to draw comparisons between these two disciplines, astrological theory is highly nuanced in practically all aspects of life, from personal development to cyclic global phenomena. There is no convincing evidence to suggest that the diverse areas of applied astrology can be understood within current psychological models or that psychological theory can encompass astrological theory. Wyman and Vyse themselves commented on important differences of context between the two disciplines. In astrological theory, the relational system of critical moments is determined by the arrangement of celestial bodies, whereas in trait psychology theory, the causes of personality are determined by the individual’s genetic profile (W&V p.287-8).

These different contexts represent a dichotomy of perspectives. The principle “as above, so below” conveys the concept that astrological properties reflect the cycles of the celestial bodies in the macro-environment and that these properties are used and developed by everyone within that environment. This context applies to a global perspective and the resilience of shared properties and needs. To many scientists, such as influential British biologist Richard Dawkins, the psychological properties selected and expressed by genes pertain to individualism, competition, reproduction, and selfishness. Each of these different contexts sustains a distinctly different set of purposes and assessments. The authors did not instruct the test subjects to judge the astrological and psychological profiles independently within their respective contexts, but instead suggested direct comparisons. This approach represented a bias against astrology. (3)

Substantive modifications

Wyman and Vyse incorporated “substantive modifications” into their experiment for changes that had occurred since the Carlson experiment (W&V, 289). The authors used a positive test strategy to improve their results for personal validation. A positive test strategy is described by psychologists Joshua Klayman & Young-Won Ha (1987) as “a tendency to test cases that are expected (or known) to have the property of interest rather than those expected (or known) to lack that property.” Although this strategy is not necessarily equivalent to confirmation bias, Klayman & Ha warn “It can, however, lead to systematic errors or inefficiencies” (Klayman & Ha, 211). 

Presumably, Wyman and Vyse intended to incorporate the latest standards and tools for the two disciplines to demonstrate, by equally easy and unbiased methods, either the presence or the absence of personal validation for both the psychological and astrological tasks in their experiment. The authors chose the NEO-FFI questionnaire and a two-choice format as a positive test strategy to make it easier for their test subjects to identify their own psychological profiles. However, the authors’ use of a CGAP to provide astrological profiles may not have been a positive test strategy.  

In his experiment, Carlson had asked reputable astrologers to write natal chart profiles for the test subjects. Skilled astrologers should be able to weigh the properties in natal charts and identify those properties that are of interest. Instead of astrologer-written profiles, Wyman and Vyse substituted a “sophisticated” CGAP, generated by the Solar Fire version 5.0.19 software program (W&V p.289). The Solar Fire software has a variety of chart comparing and analytic features, and it is capable of accurately plotting the positions of planets and asteroids over many centuries, but it also has an interpretive option that lists the basic chart properties. To justify their substitution, the authors cited an advertisement for the software and a reference from an astrological organization, the National Council for Geocosmic Research, that recommended the software for research (W&V, 291).

Wyman and Vyse did not give reasons as to why they thought their use of the Solar Fire interpretive feature was an improvement over Carlson’s use of astrologer-written profiles. They did not mention Carlson’s astrologers and avoided this issue. In some respects, however, the authors’ choices of the NEO-FFI and a CGAP might appear to be steps towards a convergence that would justify their use together. The NEO-FFI does not discriminate gender identity and is less of a diagnostic tool for mental health disturbances than the CPI questionnaire. Most astrologers would probably agree that these factors bring the NEO-FFI somewhat closer to astrology than the CPI. The Solar Fire CGAP option might appear to be justified because it was created by astrologers and seemed to present standard interpretations based on the astrological literature. Stable, standardized test instruments are what psychologists would look for. Psychologists did not write the psychological profiles, so why should astrologers have written the astrological profiles?

The problem with this argument is that astrology and psychology are different disciplines and each places a different burden of complexity and comprehension on the test subjects. Each NEO-FFI self-test result presented only five briefly described personality dimensions and an evaluation as to whether the respondent was high, moderate, or low in each of the five traits. By contrast, each CGAP, after editing by the authors, consisted of 29 one-to-four sentence descriptions of potential that each subject had to comprehend in terms of their entire life and development. The authors even conceded the greater difficulty of their subjects’ astrological task, “The computer-generated astrological reports in the present study contained many more personality descriptions—29 separate personality statements—that may have made the task more difficult than the task with the NEO-FFI” (W&V, 297). 

No one, least of all astrologers, would seriously argue that a computer program could equal the chart interpreting skills of experienced astrologers. The Solar Fire program was incapable of weighing and integrating the many pieces of interpretation as a skilled astrologer would have done. To avoid bias, the authors’ research methodology needed to equalize the complexity of the subjects’ astrological and psychological tasks. Their substitution of the CGAPs introduced greater complexity and required greater effort to understand than the astrologer-written profiles used by Carlson and this biased the experiment against their astrological hypothesis.

A sanity check

Given the use of the CGAPs, the type of edits that Wyman and Vyse made to the CGAPs needs to be examined. Astrology is a discipline with which Wyman and Vyse had little familiarity and yet which they felt confident to modify as they saw fit. The authors removed all references to astrological signs, planets, and houses from the test subjects’ CGAPs. These modifications were necessary to avoid bias due to astrological knowledge and, if those edits were done correctly, this would not have been a problem. However, the authors also removed all information related to planetary aspects. Their explanation for these edits was that some natal charts had more planetary aspects than others and this could bias the tests in favor of the longer profiles. This was not a valid reason for removing all of the aspects.

Among astrologers, the planetary aspects are probably the least controversial feature of natal charts. There are various house and sign systems in use today, but there is nearly universal acceptance of the five traditional Ptolemaic aspects, although additional aspects are sometimes also used. A natal chart is considered to be an integrated system and aspects represent the potential conflicts and resolutions between the different parts of the system and thus can be regarded as an important integrative feature. In astrological practice, aspects are not optional.

To retain aspects in the astrological profiles, the authors could have included an equal number of the most important aspects in each CGAP. However, this would assume that Wyman and Vyse would recognize which aspects were the most important. To avoid errors, the authors could have consulted expert astrologers for a sanity test or “smoke test” of what edits would have been acceptable, assuming that the CGAP substitution itself would have been acceptable. Wyman and Vyse gave no reasons for not consulting with subject matter experts (SMEs) for any of the modifications they made.

A sanity check or would also have allowed astrological SMEs to strike down an obvious misrepresentation. Wyman and Vyse misunderstood the polarities of the odd-numbered (positive, masculine) signs as “favorable” and the even-numbered (negative, feminine) signs as “unfavorable.” It appears they mistook “positive” to mean favorable and “negative” to mean unfavorable in a literal and fundamentalist sense. In astrology, favorability is contingent upon function and it is incorrect to assign sign favorability in the absolute sense that the authors did.

The authors referenced other studies by non-astrologers who claimed to have tested this presumed favorable versus unfavorable determination and they devoted a section of their article to its analysis. To further compound their mistake, the authors twice described, and presumably evaluated, the sign Aquarius as being both odd-numbered and favorable and even-numbered and unfavorable (W&V, 289, 294). The authors did not provide an astrological source for their favorable vs. unfavorable sign theory and it appears to have derived from the folklore of pseudoskeptical inquiry.

The authors’ substantive modifications to their replication of the Carlson experiment had made the psychological task easier and more efficient but made the astrological task more difficult and inefficient. These design differences in the complexity of tasks and the authors’ unverified astrological edits favored the authors’ psychological hypothesis even before the testing began.

Selecting participants with the right stuff

Students are often used as experimental test subjects at colleges and universities, yet for experiments where the students have a vested interest in the outcome, objectivity cannot be expected. Typically, students are under financial and career pressures and will avoid risks that would jeopardize the considerable investment they put into their education. Wyman and Vyse recruited students (N=52) mainly from an introductory psychology course at Connecticut College. The author Stuart Vyse was a psychology professor at that college specializing in “irrational behavior, superstition, and belief in the paranormal” (W&V, 299). The students enrolled in the psychology course received a course credit for their participation in the experiment. That incentive to earn a credit represented a bias. However tenuous, that small stake in determining the success of the experiment had potential to influence how the students performed their tasks. There were other problems as well.

The test participants were between the ages of 18 and 22 years (M age = 19.3 years). Teenagers, even those in their late teens, lead relatively sheltered lives and are not suitable subjects for the authors’ test of astrology. Suitable subjects would have a solid grasp of self-knowledge and potentials through their own self-sustaining life experiences. Only mature individuals can be expected to have these necessary qualities. For young people, concepts of self in personal relationships, place in society, and sense of life purpose are still malleable and easily influenced. The use of teenagers as test subjects, especially if the authors were in positions of authority over them, would represent a bias that would favor the authors’ hypotheses.

The students in the experiment were in college to learn psychology not astrology. Colleges and universities in Western societies do not teach courses in astrology. This institutional bias must be considered. To ensure their academic success, the students might expect that they would need to compare astrology, which would be unfamiliar to them and their professors, with psychology, which was the mutually agreed upon discourse with their professors. The authors’ assertion that psychology and astrology “share a common purpose” would only have reinforced the primacy of psychology as the chief purpose of the experiment. These institutional and primacy biases favored the authors’ psychological hypothesis. 

In their article, Wyman and Vyse devote much space to the analysis of various biases based on data gathered from their astrological knowledge and beliefs questionnaire. Three weeks before the NEO-FFI and CGAP identification tests, the students were required to provide their birth date, time, and location. They were also required to complete and sign a questionnaire that disclosed their personal astrological knowledge and beliefs. This disclosure would have signaled that the intention of the experiment was not simply to evaluate samples of astrology and psychology but also to assess personal beliefs. The signed disclosures could be seen by someone who might make judgments of “irrational behavior, superstition, and belief in the paranormal.” Wyman and Vyse did not explain how they would protect the students against the potentially frightening implications that their personal beliefs might have on their educational investments. (4)

The authors warned the students that providing inaccurate birth information or inaccurate questionnaire responses would be a violation of the honor code of the college. This warning of possible expulsion from the college could cause the students to feel vulnerable and hesitant to make disclosures that might be unacceptable to those in authority. Belief in controversial knowledge like astrology at an institution where it is not taught would not be an academic asset but could very well be a liability. If the students sensed that the experiment had raised the stakes on their openness to unconventional beliefs through the knowledge and beliefs questionnaire, then the students had the opportunity to lower the stakes by making personal rationalizations that would restore their academic safety. Without intending to influence the students or even being aware of doing so, the authors’ disclosure questionnaire may have unwittingly created biases that impacted student responses on not only the questionnaire and also the later identification tasks. (5)

In total, the authors held a powerful influence over the students through means of the course credit bias, the learning primacy bias, the institutional exclusion bias, and the beliefs liability bias. These biases would have acted in concert as psychological pressures to not only overwhelm the experiment’s beliefs disclosure but also its double-blind methodologies to the point of irrelevance. The normal facility of teenagers to rationalize all cognitive dissonance to their own immediate interests would have swayed the students’ natural curiosity for different concepts like astrology and fostered an uncritical indoctrination that served to confirm the authors’ own biases and interests. This was not a rational environment in which to conduct a scientific evaluation.

Testing and results

The students were given four profiles or summaries: their real NEO-FFI profile and a bogus NEO-FFI selected at random from the other participants, and their real CGAP and a bogus CGAP also selected at random. “(Participants rated) each statement of all four personality summaries on a 1-9 point scale. In addition, participants provided a single overall accuracy rating for each summary, and we asked them to identify which of the two NEO-FFI reports they believed was their own and which of the two astrological summaries was their own. Last, participants considered all four of the personality reports and identified the one that they thought was the more accurate description of their personality” (W&V, 292). 

Because of the number and weight of the biases in play, the experimental results for astrology can almost be guessed as a foregone conclusion and cannot be regarded as conclusive. The students identified their real NEO-FFI profiles at a rate of 78.8% (p<.001) and they identified their real CGAPs at a rate even lower than the bogus CGAPs at 46.2%. When the students rated the “most accurate” of the four profiles, the results were: real NEO-FFI 54.9% (p<.001), real CGAP 19.6%, bogus CGAP 15.7%, and bogus NEO-FFI 9.8%. A P.T. Barnum effect was found in all four personality profiles. There was no effect for the so-called “favorable versus unfavorable” sun signs. Students who knew their sun sign gave higher accuracy scores to the sun sign statements over the non-sun-sign statements. Greater knowledge of astrology produced significantly lower scores for the bogus CGAPs but had no effect on the real CGAPs. There was no effect based on belief in astrology. In similar fashion to the astrological results, belief in psychology produced higher scores for the bogus NEO-FFI profiles, but had no effect on the real NEO-FFIs. 


Lessons can be learned from the Wyman and Vyse experiment for the benefit of future Vernon Clark type matching tests. Self-test psychological profiles like the NEO-FFI and natal chart profiles do not apply to the same perspectives on life. The NEO-FFI profile can be useful for assessing groups of people, but what is its value as a tool for self-understanding if its results can be so easily identified (79%)? What deeper insights can an individual learn from it that they do not already know? By contrast, a natal chart interpretation purports to describe the native’s life potentials and their adaptations to social and everyday changes. These are more reflective concerns that are not easily understood or identified in a few minutes or hours, although mature people are much better at understanding these concerns than young people. One of the authors’ own statements stresses a useful criteria in this regard, “Still, a measure of the profile’s ability to predict future behavior would be more convincing” (W&V, 299). Why then did the authors test the natal chart profiles of young subjects who would be less certain about their future development than mature subjects who would already have experienced a greater part of their development and who could provide a more convincing measurement? 

What was the purpose of the Wyman and Vyse experiment? What did the authors expect to learn? Simply that the participants could identify and thus confirm the “validity” of their psychological and astrological profiles? The participants could have done that without the disclosures they made on the astrological knowledge and beliefs questionnaire. What Wyman and Vyse really wanted was to determine, or at least suggest, the causes of astrology. Specifically, they wanted to know whether astrology was due to the appeal of an unrealistically favorable self-image or whether it was due to a falsely personalized P.T. Barnum effect. 

Despite all their discussion, the authors’ analysis failed to demonstrate these or any other psychological causes. The authors concluded, “However, neither the present study nor Wunder’s result contradicts the basic premise that the favorableness of a personality description affects its acceptability because neither study directly measured favorability or unfavorability of the profiles” (W&V, 298). In other words, the authors’ experiment did not contradict the favorable self-image premise as a cause of astrology because they did not evaluate it. This unevaluated, uncontradicted “basic premise” in the authors’ experiment is an assumption and an example of the rational fallacy known as argument from ignorance. No one really knows, so let it be true.

What about the Barnum effect? “In the present study, we found evidence of the P.T. Barnum effect in participants’ evaluations of both the astrological reports and the NEO-FFI profiles” (W&V, 297). Hence the P.T. Barnum effect could not account for astrology any more than psychology in the experiment. Furthermore, “Those who correctly identified their astrological profile did not differ in their degree of belief in astrology” (W&V, 298). Hence the authors’ experiment with the astrological knowledge and beliefs questionnaire did nothing to explain acceptance of the CGAP or belief in astrology. This leaves open the possibility that the authors failed to find causes for astrology because they looked for the wrong causes.

It is disappointing that the authors had so little familiarity with the phenomenon that they studied. They might have developed a better experiment. Wyman and Vyse did not describe the existing literature of Vernon Clark tests other than the Carlson experiment nor did they describe the abstract principles of astrology relevant to the concrete details of their experiment. They were unappreciative of the learned skills, the methods, and the discourse used in astrology.  They did not consult astrological SMEs who could have advised them on whether their hypotheses and methods were in the ballpark. Their test of the so-called favorable versus unfavorable signs was an avoidable blunder. They failed to distinguish between the expressed traits of personality that manifest at a specific point in time and the emergent potential of character that develops over a lifetime. Instead, they suggested similarities in what amounts to a category mistake. The authors presumed they needed no familiarity with astrology because they assumed they already knew its causes and had the answers.

Although there are many deserved criticisms of the Shawn Carlson double-blind experiment, Carlson’s methodology was exemplary in some respects. As a shared flaw, Carlson, like Wyman and Vyse, did not use a sample of mature test subjects. But Carlson recruited reputable astrologers and they provided data that supported Carlson’s astrological hypothesis, as assessed by Ertel (2009). Carlson did not presume to look for any hidden psychological causes of astrology and thus he avoided the various biases that Wyman and Vyse introduced in their experiment. Because Wyman and Vyse were so concerned with causes, they did not evaluate the specific sign, house, and aspect components of the Solar Fire profiles for accuracy. Such an analysis might have provided more promising astrological insights.

Causes are nice to have in science because they enable easy prediction, but causes are not necessary for empirical observations or for new knowledge to be applied to good purpose. For the past 100 years, statistical inference has led the way in scientific research. It is not scientifically or epistemologically efficient to expect to know causes first before evaluating the evidence of correlations and relationships. In today’s science, the single-minded expectation of understanding causes and its attendant demand for a mechanism is an irrational argument and it prevents much of the astrological criticism by skeptics from being taken seriously within the scientific community.

Many thinkers, and Wyman and Vyse may be among them, recognize that individual personality is not entirely the manifestation of genes but that personality is also shaped by environment. Yet these environmental effects are most often simply acknowledged and then dropped because no one seems to know how to comparatively evaluate them for individuals with any reliability. Environmental factors remain a largely inaccessible problem of personality assessment, yet it is seldom recognized that astrology is explicitly structured as a study of how the native interacts with the environment in intimate detail.

To benefit from double-blind chart matching tests like the Wyman and Vyse experiment, it would be of interest to see which astrologers are best able to perform the matching tasks and then formulate these practices into structured concepts and theories that can be compared and methodically evaluated. Which astrologers have the best working models of aspects, signs, or houses? What parts of traditional astrological texts need to be examined and possibly updated? The informal qualitative research that astrologers typically do among themselves with case studies can be augmented by the more disciplined quantitative testing methods that Shawn Carlson implemented and Wyman and Vyse tried to improve. Future experiments should enable their participants—competent astrologers and mature test subjects—to give their best efforts in fair tests. The next experiment, which should be a true collaboration of researchers and knowledgeable astrologers, could be named “Science and Astrology: A double-blind test without bias.”


1. Two-choice versus three-choice tests becomes an issue in experiments where astrologers are asked to identify natal charts. Two-choice tests are more suitable for testing with heterogeneous samples. For example, the Vernon Clark double-blind experiment used a two-choice format to test whether astrologers could distinguish between ten sets of charts of people with cerebral palsy versus people with high intelligence. Three-choice tests, with the first two choices evaluated together, are more suitable for testing a relatively homogeneous sample that has a higher likelihood that two charts out of any given three might have insufficiently distinguishing features. For example, the Shawn Carlson double-blind experiment used a three-choice test because the sample consisted of students who were close in age and attended the same university. 

The test subjects in the Wyman and Vyse experiment were even more homogeneous than Carlson’s. Their sample consisted mainly of students in the same introductory psychology course within a narrower age range. Wyman and Vyse state, “To maximize the likelihood of correct identification, we used a simple two-choice task” (W&V, 289). However, it is more likely that the two-choice format used by the authors did not maximize the correct identifications.

2. A videoed test (c. 1999) by American researcher Michael Shermer is worth special mention because the video has only recently reappeared online on YouTube after having been taken down for over a year and could be taken down again. In the late 1990s Shermer was the publisher of Skeptic Magazine and had a TV show called Exploring the Unknown. On one of the shows, Shermer challenged American Vedic astrologer Jeffrey Armstrong to a double-blind test. Armstrong could not see or talk to the participants. He was given only the birth location, date, time, and gender of the nine participants and his three-minute readings of each participant were recorded. The readings were played to the participants and Shermer scored the accuracy of Armstrongs’ statements while Armstrong made notes while watching from another room. 

The scores for the nine participants were: 69%, 63%, 89%, 71%, 74%, 75%, 66%, 38%, and 21%. Unbeknownst to the participants or Armstrong, the readings for the last two participants had been switched. When these participants heard their real readings, the accuracy of these readings changed from 38% to 94% and from 21% to 92%. In total, the participants agreed with 105 out of 137 of Armstrong’s statements for an overall score of 77%. In the end, Shermer questioned the plausibility of the typical skeptical explanations. How should Armstrong have been able to make accurate statements 77% of the time just on generalities, logical guesses, or blind luck?

3. The argument that genes fundamentally cause personality is incomplete because it does not account for how genes themselves change. Recent research into identical twins has shown that genomic structures are not fixed but mutate and change such that twins are not as genetically identical as was once thought (Brogaard & Marlow, 2012). This explains why identical twins develop different personalities and traits. If genes are the cause of personality and yet mutate, then one needs to consider how environmental factors might empirically correlate with genetic changes and expressions of personality. Any single instance of genetic mutation could spontaneously emerge from the quantum state without an empirical cause, yet still be probable. The empirical tendencies of an organism’s quantum genetic mutations could be indeterminate and non-causal and yet be statistically measurable.

4. Judging by the figures in the authors’ intercorrelations table (W&V, 296) there were an estimated two or three participants out of the total of 52 participants who claimed astrological beliefs. These special participants may have been recruited outside of the classroom through “fliers posted around the campus” (W&V, 290) but this was not a large enough sample to be representative. According to a Gallup report by David Moor (2006), 25% of Americans believe in astrology.

5. American psychologist Bertram Forer’s influential 1949 classroom experiment into gullibility and personal validation used a deliberate confirmation bias to evoke a type of unwitting confirmation bias now commonly known as the P.T. Barnum effect. The Barnum effect is the tendency for people to regard a personality description as accurate when it appears to be unique to them, even though the description is written to be so vague that it applies to a wide range of people. 

Forer created a questionnaire that he called the DIB personality test, and administered the test to his students. A week later, immediately before a scheduled quiz, Forer asked the students to rate each description in the resultant profiles for accuracy to themselves and to hand in their signed results. Unbeknownst to his students, Forer had given each student the same profile. This profile was based on a newsstand astrology book from which Forer had intentionally selected statements to be vague and generally true for everyone. Analysis of the students’ signed results demonstrated that the students had rated their professor’s DIB test as being highly accurate. This result should come as no surprise because Forer had intentionally biased his test to confirm the effect he was looking for and because students, apart from any Barnum effect, have a known tendency please their teachers when it counts and are perhaps even more receptive to the tendency when they are just about to write a quiz. 

Similar tests have been performed countless times with various groups such as students, soldiers, and even astrological skeptics, with similar results and the Barnum effect is regarded to be a robust phenomenon (Rogers & Soule, 382). Many “rational skeptics” have argued that astrology operates by “cognitive bias” by their rationalization along the following lines: 1) The P.T. Barnum effect is the false assumption of information unique to oneself. 2) Astrology is information unique to oneself. 3) Therefore astrology is a P.T. Barnum effect. Consistent with this illogical reasoning, any information unique to anyone would necessarily be false and a Barnum effect. The assumption of a P.T. Barnum effect does not falsify astrological theory.


I am very grateful for critical input from Correlation’s peer review panel and for the advice of my associates in the astrological community. Special thanks to Anita Puronto for her editorial review for my final draft. 

Efforts were made to contact Professor Stuart Vyse for samples of the test materials and for discussion, but there was no reply. Drafts of this article were sent to Professor Christopher French and Professor Ivan Kelly for comment, but there were no replies.

© 2014 Kenneth McRitchie


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Cognitive bias in the McGrew and McFall experiment

Review of “A scientific inquiry into the validity of astrology” [Download]

This article has been peer reviewed and published by ISAR International Astrologer, 41, No. 1, pp. 31-37. Copyright © 2014 by Kenneth McRitchie. [Download PDF]

Abstract. The McGrew and McFall experiment attempted to resolve a weakness that the authors identified in Shawn Carlson’s 1985 double-blind astrological chart matching and self-selection experiment. Both the astrologers and the test subjects in Carlson’s experiment might have failed to make correct selections because of the same non-astrological problem. The authors performed a replication yet they introduced their own problems and failed to acknowledge how cognitive biases influenced their results. One of these biases was the “birthday paradox” that the authors implemented in reverse as a counter-intuitive illusion based on a Poisson distribution. This illusion acted to raise astrologers’ confidence in their abilities. Another was the known tendency for people to have overly-positive illusions about themselves that the authors implemented by using a non-standard, open-ended questionnaire. The authors also neglected to test the self-selection ability of their experimental test subjects, thereby ignoring their own criteria of validity and the justification for their experiment.

The double-blind experiment, “A scientific inquiry into the validity of astrology” by psychology professors John N. McGrew and Richard M. McFall (1990), herein referred to as “the authors,” has long stood as one of the definitive tests against astrology. The Dutch researcher Rob Nanninga (1996) gave the experiment additional weight by his successful replication. Australian statistician Geoffrey Dean and Canadian psychologist Ivan Kelly described the experiment and its replication in their influential study “Is Astrology Relevant to Consciousness and Psi” (2003). For them, the McGrew and McFall experiment was convincing evidence that they used to support their arguments against astrology.

The McGrew and McFall experiment was intended to cover what its authors regarded to be a “methodological inadequacy” in Shawn Carlson’s (1985) famous double-blind test of astrology published in Nature. Carlson had tested whether reputable astrologers (N=29) could accurately identify the California Psychology Inventory (CPI) profiles of test subjects (N=100+ mostly University of California at Berkley students). For each subject’s natal chart, the astrologers were given the real CPI profile and two others randomly chosen from the other subjects. The astrologers were asked to rate the individual sections of the three CPIs compared to the natal chart and then to rank their first, second and third choice CPI. By using the same rating and ranking procedure, Carlson tested whether each test subject could identify their own natal chart profile, written by the astrologers, which they had to choose from two others. Also by the same procedure Carlson asked the test subjects to identify their own CPI profiles from two others. (1)

In his analysis, Carlson found that the astrologers did not perform their tasks any better than chance expectancy. For the test subjects’ tasks, Carlson became suspicious of the rating task and discarded the data. The astrologers never learned how well they performed on the individual sections of their written profiles. Although the results for the test subjects’ ranking task (first, second, and third choice) was unusual, Carlson accepted that data. That task had a control group whose members were not given their real astrological profiles, yet the control group successfully chose the pre-selected profiles at a significantly low probability against chance (p<.01, where significance is p<.05), whereas the actual test subjects chose their profiles at chance expectancy. Carlson attributed the surprising result for the control group to a “statistical fluctuation.” Carlson also found that the test subjects could not identify their own CPI profiles any better than would be expected by chance.

Despite these negative results for both the astrologers and the test subjects, the discarded data, and the statistical anomaly, Carlson concluded, “We are now in a position to argue a surprisingly strong case against natal astrology as practiced by reputable astrologers” (Carlson, 425).

The Carlson experiment has been controversial and its strengths and weaknesses have been discussed in various papers (Currey, 2011; McRitchie, 2011; Ertel, 2009; Vidmar, 2008; McGrew & McFall, 1990). For their part, McGrew and McFall argued that because Carlson’s test subjects had failed to identify their own CPI profiles, the astrologers might have failed to match natal charts to CPIs for the same non-astrological problem. Both the astrologers and the test subjects might have had difficulty in understanding the terminology and the graphical scales that the CPI used to describe personality and traits. The evidence required to validate the Carlson experiment, the authors argued, was inconclusive (M&M, 76).

More recently than McGrew and McFall’s 1990 paper, German psychologist Suitbert Ertel (2009) published a critical review of Carlson’s experiment in which he raised the serious issue that Carlson did not actually test his hypothesis but had incorrectly calculated his analysis. Ertel tested the stated hypothesis using Carlson’s data and, in a remarkable turnabout, the evidence showed that the astrologers had successfully matched the CPI profiles to natal charts in their two tasks at a statistically significant probability (p=.054 marginal, and p=.037). To this date, Ertel’s reassessment and the discovered evidence have remained unchallenged. As an intriguing example of scientific reversal, the Carlson experiment has since become one of the leading scientific studies in support of astrology.

Avoiding some biases but not others

The changed fortunes of the Carlson experiment occurred years after McGrew and McFall conducted their experiment and the authors could not know what would happen. McGrew and McFall were concerned with a specific weakness in the Carlson experiment. They designed their own independent research that stands as a separate inquiry into whether astrology is scientifically valid. The transformation of Carlson’s evidence did not directly affect the McGrew and McFall research and this is why their experiment deserves critical review.

To study the weakness they identified, McGrew and McFall, like Carlson, recruited a group of astrologers (N=6)  and a group of test subjects (N=23). However, unlike Carlson, they tested the identification abilities of the astrologers only. Although the authors could have done so, they did not test whether their test subjects could identify their own natal chart profiles that the astrologers could have written. Carlson had understood that such a test would be close to what astrologers actually do in practice and this would ensure the validity of his experiment. It is therefore disappointing that McGrew and McFall did not replicate this part of Carlson’s experiment. Even more so because Carlson had rejected this part of his data, other than a result that contained a large anomaly. Because the authors’ experiment did not test a method that was close to what astrologers do in practice and they did not try to resolve the anomaly, this represented a bias against astrology. McGrew and McFall gave no reasons for not testing their own test subjects.

McGrew and McFall developed their experimental protocol with the participation and approval of the six participating astrologers, all members of the Indiana Federation of Astrologers. Each astrologer would be asked to match the birth charts of the 23 test subjects to 23 packages of information, which included face photographs, for the subjects. To eliminate age clues, all 23 subjects were aged 30 or 31. This narrow age range meant that there was some similarity in the subjects’ astrological charts, which would make them difficult to differentiate. The information package for each subject was extensive, including answers to 61 personal, open-ended questions that the authors had asked the astrologers to create. Besides the photographs and the 61 questions, the package included important life events and the results of the two standardized psychological tests. The authors called their resultant information package the Personal Characteristics and Life History Summary (PCLHS).

The 61 questions in the PCLHS asked about such personal lifestyle characteristics that astrologers may be concerned with, including “hobbies, interests, religious beliefs, physical characteristics, personal talents and achievements, family background, dates of parent or sibling deaths, dates of moves across the country, health problems, attitudes toward authority, sex and commitment, pet peeves, favorite colors, punctuality, dependability, and variations in the personal energy cycle” (M&M, 77).

In the McGrew and McFall experiment or any double-blind test of astrology, care must be taken to ensure that preconceptions regarding astrology do not bias the results. This precaution applies to the experimenters themselves as well as to the test subjects. However, unlike Carlson, who isolated his own influence and carefully screened out subjects who had strong opinions about astrology, McGrew and McFall did not follow a similar test protocol. They did not try to avoid their own sampling bias when they selected a sample of test subjects from the respondents to their newspaper advertisement.

Instead of screening their test subjects for bias, McGrew and McFall relied on a cover story, but this method was not robust and provided leading clues. The authors told their test subjects that the research was about the possible effects of hormone levels associated with the diurnal cycle during birth and the subsequent development of children (M&M, 79). Each test subject had to provide certified documentation of the precise date, time, and place of their birth. The 61 questions in the PCLHS asked the subjects to describe very personal information and life events of the sort that would have been familiar from popular astrology columns. Referring to these questions, the authors state, “Neither the CPI nor any other standard psychological instrument contains this type of information” (M&M, 77). When asked after the test, two of the 23 subjects said they had guessed that the experiment was about astrology (M&M, 79). Evidently, the experiment’s cover story did not provide a reliable screen for potential biases.

A statistical illusion

In addition to the above weaknesses, an even more serious problem was that the design of the experiment included a statistical peculiarity that can bias an experiment, whether the content is astrology or anything else. In the Carlson experiment and its forerunners, participants tried to match each natal chart against a set of only two (Clark, 1961) or three (Marbell, 1981; Carlson, 1985) personality descriptions. The chance expectancy for each choice in these tests was always the same and did not diminish. The matching protocol that McGrew and McFall used in their experiment employed a known cognitive bias, a mathematical illusion.

By selecting specifically 23 test subjects, the authors seem to have been aware of the counter-intuitive effect known as the “birthday problem” or “birthday paradox” (Ma, 2010). Due to a cognitive bias, we do not expect that out of 365 days in a year there is at least a 50% chance of finding matching birthdays in any group of only 23 people. However, if we go in the opposite direction, it seems intuitively easy to confidently match at least 50% from one group of 23 to another group of 23 where we know that all members in the two groups have matches. The actual probability of making half of the matches is not 50% but nearly zero. The authors reinforced this illusion of overconfidence by stating that there were only “23 possibilities” in their experiment (M&M, 82).

The reason for the illusion is that matching problems, where each attempt removes a member from each group, fall into a Poisson distribution. Counter-intuitively, the chance of finding the matches converges quickly to very small, very similar probabilities regardless of the number of pairs to be matched, whether it is 10, 23, or 200. The probability of making 1 match is approximately .37, of 2 matches is .18, of 3 matches is .06, of 4 matches is .015, and of 10 matches is .0000001 (Ma, 2010). There is a high sensitivity to error that quickly escalates with each attempt. The probability of matching all 23 pairs is vanishingly small. For the results to reach the level of statistical significance, assuming significance at p<.05, the astrologers needed to match an average of slightly more than three charts. The authors did not suggest that they knew their method created an illusion of overconfidence and they did not warn the astrologers. They gave no reasons for changing the test design that Carlson and others had used, where this illusion was not possible.

Idiosyncratic strategies

Each astrologer worked alone to match each of the 23 charts with the corresponding 23 PCLHSs. The authors did not publish any tables or graphs of their test data and it is not possible to scrutinize the mean values of correct matches. The authors reported that correct matches ranged from zero to three with a median value of one match and none of the astrologers performed better than chance (M&M, 80). The astrologers had rated their confidence at a mean value of 73.5%, which implied making at least six correct matches. The correlation between their accurate matches and their confidence was non-significant (Pearson correlation r=.03). The authors found that the results were inconsistent among the astrologers in both their correct and incorrect matches, with a mean value of only 1.4 agreements for the 23 test cases, which was not significant (M&M, 81). Importantly, as the authors pointed out, the astrologers had adopted idiosyncratic strategies, as evidenced by the hodgepodge of questions they provided for the PCLHS and their lack of agreement in making matches (M&M, 81).

This observation of idiosyncratic strategies is crucial to understanding the results. One must ask why the astrologers made the unusual departure from their normal practice. Astrology texts contain descriptions of personality and potential development for the different natal chart configurations. These are fairly standard in agreement and astrologers normally apply these descriptions in their chart interpretations. However, McGrew and McFall did not ask the astrologers to interpret any natal charts but only to match them. If the astrologers did not interpret charts, then whose personality interpretation skills were being tested?

It is normal for astrologers to simply tell their clients what their personality, character development, achievements, and other potentials can be, based on what the astrological literature says about natal charts. These areas of personal potential may or may not have been acted upon, and it is up to the client to recognize their patterns of behavior and lifestyle through the consultative process. It is not normal for astrologers to ask clients to describe their own potentials. It is not normal for astrologers to use a questionnaire to ask clients about their potentials. Applied astrology does not assume that clients know their potentials. The McGrew and McFall experiment went against normal astrology and this represented a bias against the astrologers.

The authors’ experimental design reversed the astrologer and client roles. It placed the interpretive discipline on the wrong party. The test subjects had to describe their own potentials (normally done by the astrologer) by answering an ad hoc questionnaire that McGrew and McFall required the astrologers to create. The astrologers then had to judge the accuracy and usefulness of the descriptions they received (normally done by the client).

Astrology is concerned with providing descriptions of one’s personal potentials and how to make the best choices at different stages in life. This is not the same sort of information that is generated by psychological tests, which typically only measure the dimensions of personality traits. The astrologers in the McGrew and McFall experiment might have had the best intentions but they were given an enormous task. In their attempt to create a questionnaire that would cover the entire spectrum of human potential, the astrologers tended to adopt idiosyncratic strategies and they resorted to open-ended questions, perhaps hoping that the test subjects could provide enough insight into themselves through their own self-descriptions and narratives.

The problem with this approach is that it introduced an additional cognitive bias that astrological chart readings normally prevent. Psychological studies have shown that people tend to hold unrealistically positive illusions about themselves (Taylor and Brown, 1988). For example, tests have consistently shown that almost 80% of drivers perceive themselves as being in the top 50% in terms of driving skills (McCormick, Walkey and Green, 1986). Of course this is not mathematically possible. Positive illusions of self image in virtually all areas of life are not what astrologers would want to hear, but by asking non-standard open-ended questions about personal potential and interests, these were very likely the types of responses the astrologers got. The authors’ research methodology implemented a cognitive bias that worked against the astrologers.


Because the astrologers accepted McGrew and McFall’s suggestion of creating questions for an ad hoc questionnaire, they accepted a flawed methodology and by their participation they committed themselves to the authors’ test design. McGrew and McFall did not suggest that they knew their questionnaire was open to the bias of positive self-illusion, and they did not warn the astrologers. This bias and the Poisson mathematical effect were cognitive biases or non-intuitive illusions that the authors introduced. These biases did not exist in the designs of prior double-blind astrological experiments, including the Carlson experiment that the authors were replicating.

Unlike the idiosyncratic, open-ended questionnaire created for the McGrew and McFall experiment, the Carlson experiment had used only the standardized CPI questionnaire. Ertel’s reassessment of Carlson’s experiment showed that the astrologers were able to use the CPI profiles to identify natal charts at a statistically significant probability (Ertel, 2009). Although astrologers are not in the habit of using standard psychological questionnaires, the positive results of the Carlson experiment suggest that McGrew and McFall’s astrologers might have fared better if they had restricted their evaluations to the information from the two psychological tests included in the PCLHS and ignored their own questionnaire. Standardized multiple-choice questionnaires force respondents to make specific choices and thereby reduce illusions of self image. Judging by Ertel’s reassessment of Carlson’s test, it is conceivable that targeted testing programs might show correlations between some astrological chart patterns and profiles from standardized personality questionnaires.

Although the astrologers used the information from the two psychological questionnaires to help identify charts, McGrew and McFall did not ask their test subjects to identify their own psychological profiles, as had been done in prior double-blind experiments. This missing psychological validation protocol presents a serious problem for the authors because it is uncertain how much the astrologers relied, or should have relied, on these psychological profiles. This uncertainty raises the same “methodological inadequacy” question that the authors identified in the Carlson experiment. The astrologers might have failed in their task for the same non-astrological reasons as before. Remarkably, by failing to test the test subjects, the authors did not try to resolve the psychological validation problem that they used to justify their experiment! Consequently, by their own reasoning the authors would have to judge their own experiment as equally inconclusive as Carlson’s.

Lessons to be learned

McGrew and McFall conclude their article with a sweeping rationalization. “Because each individual is unique, in practice an astrologer must use the birth information to ‘select’ the one correct interpretation that uniquely matches that individual from nearly countless possibilities, not just from 23 possibilities. Thus, our task can be seen as a simplification of the task that astrologers routinely undertake as a part of their daily practice” (M&M, 81-82).

This claim reverses the complexity of the astrologers’ normal practice compared to their tasks in this experiment. The claim that astrologers in practice must “select” a unique hit from countless possibilities of combined chart features is a misrepresentation. Astrologers read natal charts in much the same way as one would read any other type of map that has clear reference points, desired destinations, and indicators of opportunities and hazards. As anyone can understand, there is more than one way to read a map and reach a goal. Matching 23 pairs was not a simplified task and McGrew and McFall made a misleading claim. There were only 23 possibilities provided each match was performed correctly. The number of possible mismatches was staggering and cognitively incredible.

A replication the McGrew and McFall experiment was performed in 1996. Dutch researcher Rob Nanninga modeled his “Astrotest” double-blind experiment directly on the McGrew and McFall experiment and it contained all the same problems. Nanninga challenged 50 Dutch astrologers to correctly match seven natal charts to seven sets of personal information. In similar fashion to the McGrew and McFall experiment, Nanninga developed his questionnaire of non-standardized open-ended questions from ideas gathered from the participating astrologers. The questionnaire covered personal interests and background such as education, vocation, hobbies, interests, main goals, personality, relationships, health, religion, and so on, plus dates of important life events. To these, Nanninga added 24 multiple-choice questions taken from a standard personality test (Nanninga, 1996/97). Needless to say, the astrologers did not succeed in matching the charts any better than in the McGrew and McFall experiment.

Astrologers, students, researchers, and critical thinkers can learn from the McGrew and McFall experiment. The authors appeared to follow a strict scientific methodology by presenting an impressive analysis of their data. Yet, the authors failed to implement basic scientific protocols against biases, which they introduced through their test subject selection process, a Poisson matching process, and an ad hoc questionnaire of open-ended questions. The authors failed to evaluate the validity of their psychological test methodology, the very same problem that they had identified as the “methodological inadequacy” in the Carlson experiment that they used to justify their research. For these reasons the McGrew and McFall experiment can be regarded as inconclusive and might even qualify as a notable example of cognitive bias in a scientific experiment.

In retrospect, it is enlightening to read the authors’ account of how they worked their way through a “protracted negotiation period” to gradually gain entry and eventually win the trust of the initially skeptical astrologers. “The astrologers, understandably, were wary of becoming involved with research that might be biased against them or that would provide no opportunity for success” (M&M, 77). At least the authors were understanding towards the astrologers.


I am grateful to David Cochrane and Mark Urban-Lurain for their help on the birthday problem and Poisson distributions. I wish to thank International Astrologer for critical peer review, which provided valuable clarifications and suggestions.

Drafts of this article were sent to Professor Ivan Kelly and to Professor Christopher French for comment, but there were no replies.


1. The “profile self-selection” experiment authored by Neil Marbell in 1981, a forerunner leading to the Carlson experiment, attempted to methodically standardize the astrological interpretations presented to the test subjects in a way that the Carlson experiment did not do.
“The personality profiles were composed by individual astrologers from birth data alone, using all of the basic Ptolemaic factors of chart interpretation. Each profile was then revised by a committee of five astrologers, also blind to the subjects. This revision was necessary to review the interpretations and to make the profiles uniform in style, content, and overall presentation.” (Marbell, 1981, p. 4). 
Marbell claimed his experiment to be definitive in its successful outcomes, with high percentages of the subjects selecting their own chart interpretations from three presented. Despite the high percentages, the statistical probabilities of two of the tests were not significant (assuming significance at p<.05) due at least in part to the very small numbers of test subjects (N=5 or 6). Test 1 (using rigorous profiles in a laboratory setting): N=5, with 100% correct responses, and p<.000001. Test 2 (using less detailed profiles, mailed to subjects’ homes): N=6, with 66-2/3% correct responses and p=.1. Test 3 (biorhythm cover story, using both rigorous and less detailed profile items, conducted in subjects’ workplaces): N=5, with 75% correct responses, and p=.111. The Marbell experiment was notable for its cross-disciplinary participation, involving the design and review assistance of leading astrologers, notable academics, prominent skeptics, and even U.S. congressional representatives.

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© 2014 Kenneth McRitchie