Summary of PSYCOLOQUY topic Social Bias

Topic:
Title & AuthorAbstract
9(46) THE BET ON BIAS: A FOREGONE CONCLUSION?
Target Article by Krueger on Social Bias
Joachim Krueger
Department of Psychology
Brown University, Box 1853
Providence, RI 02912
USA
http://www.brown.edu/Departments/Psychology/faculty/krueger.html

Joachim_Krueger@Brown.edu
Abstract: Social psychology has painted a picture of human misbehavior and irrational thinking. For example, prominent social cognitive biases are said to distort consensus estimation, self perception, and causal attribution. The thesis of this target article is that the roots of this negativistic paradigm lie in the joint application of narrow normative theories and statistical testing methods designed to reject those theories. Suggestions for balancing the prevalent paradigm include (a) modifications to the ruling rituals of Null Hypothesis Significance Testing, (b) revisions of what is considered a normative response, and (c) increased emphasis on individual differences in judgment.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

9(49) CHARACTERIZING INDIVIDUAL STRATEGIES ILLUMINATES NONOPTIMAL BEHAVIOR
Commentary on Krueger on Social-Bias
Robert M. Hamm
Department of Family and Preventive Medicine
University of Oklahoma Health Sciences Center
900 NE 10th St.
Oklahoma City OK 73104 USA
http://www.fammed.ouhsc.edu/robhamm/index.html

robert-hamm@ouhsc.edu
Abstract: It may be good, as Krueger proposes, to test two theories with specific predictions against one another, rather than "people reason ideally" (one specific point) against "people are biased" (all other points). But the kind of theory is very important. An example with multiple specific predictions is described. Because of its theoretical framework, it was able to yield useful conclusions.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

9(51) INTELLIGENCE IS NOT RATIONAL
Commentary on Krueger on Social-Bias
Neil W. Rickert
Department of Computer Science
Northern Illinois University
DeKalb, IL 60115
http://ux.cs.niu.edu/~rickert/

rickert@cs.niu.edu
Abstract: Krueger is concerned with psychological experiments which purport to show that humans are irrational. He argues that the experimental results are partly the outcome of unwise experimental design. While granting Krueger's point, I suggest that the problem is more basic. The very idea of rational behavior, as it is usually conceived, is incompatible with what we understand as human intelligence.

Keywords: creativity, intelligence, norm, rationality.

9(57) LOGIC, INTUITION, AND EINSTEIN
Commentary on Rickert on Krueger on Social-Bias
Howard Margolis
Harris School
University of Chicago
Chicago IL 60637
http://www.harrisschool.uchicago.edu/Tycho.html

hmarg@uchicago.edu
Abstract: Rickert (1998) argues that concerns about rationality are misplaced, since creativity is not reducible to rationality. His Einstein example, however, suggests how limited that claim is.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

9(60) RATIONALITY, CREATIVITY AND KNOWLEDGE
Commentary on Margolis on Rickert on Krueger on Social-Bias.
Neil W. Rickert
Department of Computer Science
Northern Illinois University
DeKalb, IL 60115
USA
http://ux.cs.niu.edu/~rickert/

rickert@cs.niu.edu
Abstract: Margolis (1998) suggests that my claim about intelligence and rationality (Rickert 1998) was quite limited. I restate my claim in a way that should underscore its generality.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

9(68) RATIONALITY IS INTELLIGENT
Reply to Rickert on Krueger on Social-Bias
Joachim Krueger
Department of Psychology
Brown University, Box 1853
Providence, RI 02912
http://www.brown.edu/Departments/Psychology/faculty/krueger.hml

Joachim_Krueger@Brown.edu
Abstract: Rickert (1998a) argues that intelligent behavior ought to be the primary object of interest in psychological studies. Because, by his definition, creative behavior is far closer than rational behavior to the core of intelligence, little can be learned from studies of rationality. I argue instead that rational behavior is an important component of intelligence. Moreover, this component is easier to identify and more tractable than its creative cousin. Hence, I remain hopeful that the study of (ir)rationality in social contexts can be improved along the methodological lines suggested (Krueger 1998a).

Keywords: creativity, intelligence, norm, rationality

9(69) APPLYING WHAT WE HAVE LEARNED:
UNDERSTANDING AND CORRECTING BIASED JUDGMENT
Commentary on Krueger on Social-Bias
John Ruscio
Department of Psychology
Elizabethtown College
Elizabethtown, PA 17022

rusciojp@acad.etown.edu
Abstract: Decades of research on human judgment and decision making have demonstrated the presence of cognitive biases. This literature has led to a negative view of our judgmental capacities, a view that Krueger (1998) laments. However, the road to a more positive perspective first requires a clearer picture of the extent of bias and of methods for combating it. Rather than continue to debate the existence of biases, we should strive to understand their prevalence and magnitude, catalog them by source, and address them through corrective procedures. Some of Krueger's suggestions appear highly relevant for these goals.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

9(70) GETTING TO THE CORE OF THE DATA BY TESTING AGAINST ALTERNATIVE HYPOTHESES
Reply to Hamm on Krueger on Social-Bias
Joachim Krueger
Department of Psychology
Brown University, Box 1853
Providence, RI 02912
http://www.brown.edu/Departments/Psychology/faculty/krueger.html

Joachim_Krueger@Brown.edu
Abstract: Hamm (1998) endorses and elaborates two of the suggested remedies for ritualistic null hypothesis testing, namely, (1) testing alternative substantive hypotheses and (2) attempting to account for individual differences in judgment. However, the empirical example offered as an illustration of these methods appears to confuse rather than clarify them. I offer a counterexample from research on social projection to illustrate both remedies and to underscore the point that they offer distinct benefits which can be observed within the same data set.

Keywords: hypothesis testing, Bayes' Rule, rationality, projection.

9(71) THE BET ON BIAS IS COCKEYED OPTIMISM
Commentary on Krueger on Social-Bias
Clark McCauley
Psychology Department
Bryn Mawr College,
Bryn Mawr, PA 19010
phone (610)526-5017
fax (610)526-7476

cmccaule@brynmawr.edu
Abstract: Bayesian statistics have drawbacks beyond subjectivity of prior probabilities, and attribution research probably suffers more from ignoring man the lawyer than from ignoring subjects' beliefs about the power of situational causes. More importantly, the root of social psychology's focus on errors and biases is an unwarranted optimism that human conflict will diminish if we can see one another more accurately.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

9(73) THEORETICAL PROGRESS REQUIRES REFINED METHODS AND THEN SOME
Reply to Ruscio and McCauley on Krueger on Social-Bias
Joachim Krueger
Department of Psychology
Brown University, Box 1853
Providence, RI 02912
http://www.brown.edu/Departments/Psychology/faculty/krueger.hml

Joachim_Krueger@Brown.edu
Abstract: Can research on social-perceptual biases benefit from improved and diversified statistical methods? Having reached the brink of nihilism, I conclude that (a) any point-hypothesis can be rejected by null hypothesis significance testing (NHST), (b) any such hypothesis can be accepted by Bayesian inference, (c) effect size estimates are meaningful only if that meaning is imported from extra-statistical considerations, and (d) taxonomies of biases and their causes will be messy because most biases are overdetermined.

Keywords: hypothesis testing, Bayes' Rule, effect sizes, projection

9(75) INDIVIDUAL DIFFERENCES IN COGNITIVE BIASES
Commentary on Krueger on Social-Bias
Keith E. Stanovich
Department of Human Development and Applied Psychology
University of Toronto
252 Bloor St. West
Toronto, Ontario
Canada M5S 1V6
http://www.oise.utoronto.ca/

kstanovich@oise.utoronto.ca
Abstract: Krueger is right to call for more flexible statistical methods when evaluating cognitive biases and for a consideration of individual differences. A programmatic series of studies on individual differences in rational thought (Stanovich, in press) illustrates how patterns of covariance among reasoning biases -- as well as patterns of covariance among biases and indices of cognitive ability -- can help to reveal when discrepancies between normative and descriptive models are due to performance errors, to computational limitations, and to the misapplication of normative models by experimenters. Patterns of individual differences have implications for alternative explanations of the gap between normative and descriptive models of human behavior.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

9(77) WHAT CAN INDIVIDUAL DIFFERENCES IN REASONING TELL US?
Reply to Stanovich on Krueger on Social-Bias
Joachim Krueger
Department of Psychology
Brown University, Box 1853
Providence, RI 02912
http://www.brown.edu/Departments/Psychology/faculty/krueger.hml

Joachim_Krueger@Brown.edu
Abstract: The study of individual differences in social-perceptual biases can illuminate both normative models of judgment and patterns and co-occurrences among biases. Empirical research on the latter is especially important because some hasty claims about the relationships among biases have already been made. The putative mutual exclusivity of social projection and self-enhancement serves as an illustration.

Keywords: individual differences, cognitive biases, projection, self-enhancement

10(001) THE HAZARDS OF MECHANICAL HYPOTHESIS TESTING
Commentary on Krueger on Social-Bias
Mark Hallahan
Department of Psychology
Clemson University
Clemson, SC 29634-1511
http://hubcap.clemson.edu/psych/publish-hallahan.html

mhallah@clemson.edu
Abstract: Researchers often use null hypothesis significance testing without considering important issues such as statistical power and whether statistical tests' underlying assumptions fit their theory and data. This commentary discusses how these issues relate to research on lay perceptions of streak shooting. It is suggested that researchers may better understand their phenomena explicitly trying to model them, consciously recognizing the inherent biases and limitations of their methods and choosing methods flexibly to fit the specific attributes of their data and theory.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

10(004) THE HOT HAND AS A TESTABLE HYPOTHESIS
Reply to Hallahan on Social-Bias
Joachim Krueger
Department of Psychology
Brown University, Box 1853
Providence, RI 02912
http://www.brown.edu/Departments/Psychology/faculty/krueger.hml

Joachim_Krueger@Brown.edu
Abstract: The pervasiveness of the belief in the hot hand in basketball is widely accepted. There is less agreement regarding the reality of this phenomenon in the basketball court. It is here that null hypothesis significance testing (NHST) can make a contribution. Rather than testing whether a random model perfectly predicts performance, one can test whether there is a significant directional effect. The null hypothesis is thus not a meaningless point hypothesis, but the upper bound of half the available continuum (which represents the cold hand).

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

10(006) IN DEFENCE OF SIGNIFICANCE TESTS
Commentary on Krueger on Social-Bias
Siu L. Chow
Department of Psychology
University of Regina
Regina, Saskatchewan
Canada S4S 0A2

Siu.Chow@uregina.ca
Abstract: Krueger argues that hypotheses in favour of human irrationality benefit from the shortcomings of using significance tests. This underscores the need to distinguish between (a) theory-corroboration and utilitarian experiments, (b) the substantive and statistical hypotheses, (c) corroborating explanatory theory and testing statistical hypothesis, and (d) two levels of abstraction.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

10(015) SIGNIFICANCE TESTING DOES NOT SOLVE THE PROBLEM OF INDUCTION
Reply to Chow on Krueger on Social-Bias
Joachim Krueger
Department of Psychology
Brown University, Box 1853
Providence, RI 02912
http://www.brown.edu/Departments/Psychology/faculty/krueger.hml

Joachim_Krueger@Brown.edu
Abstract: Chow (1999) presents an "if only" defense of Null Hypothesis Significance Testing (NHST). If investigators only recognized the distinctions between (1) theory corroboration experiments and utilitarian experiments, and between (2) substantive hypotheses and statistical hypotheses, then NHST could take its rightful place in empirical psychology. By contrast, I suggest that these distinctions divert attention away from the fundamental problems of NHST, namely, that (1) point-specific hypotheses (null or other) cannot be verified, and that (2) increases in statistical power favor any non-null hypotheses and hence the substantive claims associated with them.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

10(027) STATISTICAL MODELS AND STRONG INFERENCE IN SOCIAL JUDGMENT RESEARCH
Commentary on Krueger on Social-Bias
John Ruscio
Department of Psychology
Elizabethtown College
Elizabethtown, PA 17022

rusciojp@acad.etown.edu
Abstract: In debating whether an asymmetry in traditional null hypothesis significance testing (NHST) biases empirical results against human rationality, the limited role that NHST can play in scientific reasoning has been overlooked. Platt's (1964) framework of "strong inference" illustrates the proper use of NHST and the interpretation of its results, chiefly the ruling out of one potential alternative explanation for observed data (usually chance-level differences or associations). Especially in light of this limited role that NHST can play, it is critical to use an appropriate statistical model. The inconclusiveness that can result from using an incorrect model is discussed in the context of social projection.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

10(046) INFERENTIAL STATISTICS ARE DESCRIPTIVE
Commentary on Krueger on Social-Bias
N. Sriram
Department of Social Work & Psychology
The National University of Singapore
11, Law Link, Singapore
Republic of Singapore

sriram@nus.edu.sg
Abstract: NHST is a useful tool for communication among researchers at the frontiers of scientific knowledge. I contend that inferential statistics are used primarily as descriptive landmarks in negotiating uncertain terrain, and that fashioning suitable null hypotheses can be nontrivial. Momentum effects in tennis are served as an example. Research advances both by both magnifying and isolating effects, and p values are valuable benchmarks in this endeavour. An increased focus on the locus of effects at the level of the individual is desirable. These recommendations are orthogonal to the abstract logic underlying NHST and do not diminish its utility.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

10(066) DO WE NEED INFERENTIAL STATISTICS?
Reply to Sriram on Krueger on Social-Bias
Joachim Krueger
Department of Psychology
Brown University, Box 1853
Providence, RI 02912
http://www.brown.edu/Departments/Psychology/faculty/krueger.html

Joachim_Krueger@Brown.edu
Abstract: The distinction between descriptive and inferential statistics is indeed artificial. Sriram (1999) stresses the descriptive value of test statistics and their associated p values. I support his proposal and present a Bayesian argument (and example) for the connection between p values and coefficients of replicability. I also agree with the view that much implicit Bayesianism can be detected in the day-to-day operation of research workers. Coaxing this ghost out of the closet, I think, would make social psychological research 'more positive'.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

11(028) BIASES TO THE LEFT, FALLACIES TO THE RIGHT:
STUCK IN THE MIDDLE WITH NULL HYPOTHESIS SIGNIFICANCE TESTING
Commentary on Krueger on Social-Bias
Ralph Hertwig & Peter M. Todd
Center for Adaptive Behavior and Cognition
Max Planck Institute for Human Development
Lentzeallee 94
14195 Berlin, Germany
http://www.mpib-berlin.mpg.de/ABC/Staff/hertwig
http://www.mpib-berlin.mpg.de/users/ptodd

hertwig@mpib-berlin.mpg.de ptodd@mpib-berlin.mpg.de
Abstract: Krueger (1998) argues that biases are simple to find because of the ease of disproving overly specific null hypotheses of normative behavior. We support his argument with examples of biases falling on both sides of the normative null hypothesis in behavioral decision making, and we show how a broader definition of normativity can lead to opposite conclusions about human rationality. To overcome the problems of asymmetric hypothesis testing -- encouraging the discovery of biases and discouraging the specification of particular cognitive processes -- we recommend two steps: submit precisely specified theories to symmetrical tests, and model sound reasoning based on problem-specific psychological assumptions.

Keywords: biases, heuristics, narrow norms, Bayesian reasoning, autocorrelation, symmetric hypothesis testing

11(051) THREE WAYS TO GET TWO BIASES BY REJECTING ONE NULL
Reply to Hertwig & Todd on Krueger on Social-Bias
Joachim Krueger
Department of Psychology
Brown University, Box 1853
Providence, RI 02912
http://www.brown.edu/Departments/Psychology/faculty/krueger.html

Joachim_Krueger@Brown.edu
Abstract: When the null hypothesis of rational responding is sandwiched between "biases to the left [and] fallacies to the right" (Hertwig & Todd, 2000), its cause is lost. Opposite biases can be "detected" in three different scenarios: (1) multiple studies performed in different research paradigms, (2) multiple studies performed in a single paradigm, and (3) single studies performed in a single paradigm. In the first two scenarios, moderator variables offer useful information that can take research beyond significance testing. The third scenario, however, harbors the deepest prejudice against demonstrations of human rationality. Here, regression artifacts are easily misinterpreted as evidence for the co-existence of opposite biases.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

11(123) WHY THE BIAS TO STUDY BIASES?
Commentary on Krueger on Social-Bias
Andrew Ward
Department of Psychology
Swarthmore College
500 College Ave.
Swarthmore, PA 19081

award1@swarthmore.edu
Abstract: I agree with Krueger (1998) that social psychologists place disproportionate emphasis on errors and biases in social perception, often neglecting instances in which lay perceivers offer appropriate and reasonable responses. Yet even if Krueger is correct in asserting that such errors are rarer than portrayed in the social psychological literature, there are still valid reasons for studying them.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference

12(009) SOCIAL BIAS ENGULFS THE FIELD
Reply to Ward on Krueger on Social-Bias
Joachim Krueger
Department of Psychology
Brown University, Box 1853
Providence, RI 02912
http://www.brown.edu/Departments/Psychology/faculty/krueger.hml

Joachim_Krueger@Brown.edu
Abstract: Ward (2000) justifies contemporary research on social-perceptual biases by suggesting that biases are rare and that they, because of their rarity, reveal the properties of the social-perceptual apparatus. I take this argument to mean that social biases are analogous to visual illusions: odd but informative. Sometimes, this analogy works, but as a general theoretical platform, it is inadequate. I address this epistemic disagreement by disputing three of Ward's specific claims. Pragmatically, however, I agree with Ward on that some biases demand attention because they yield large effects and undesirable social consequences.

Keywords: Bayes' rule, bias, hypothesis testing, individual differences probability, rationality, significance testing, social cognition, statistical inference