We examine the claim that the methodology of psychology leads to a bias in animal cognition research against attributing “anthropomorphic” properties to animals . This charge is examined in light of a debate on the role of folk psychology between primatologists who emphasize similarities between humans and other apes, and those who emphasize differences. We argue that while in practice there is sometimes bias, either in the formulation of the null hypothesis or in the preference of Type-II errors (...) over Type-I errors, the bias is not the result of proper use of the Neyman and Pearson hypothesis testing method. Psychologists’ preference for false negatives over false positives cannot justify a preference for avoiding anthropomorphic errors over anthropectic errors. (shrink)

Unfortunately, reading Chow's work is likely to leave the reader more confused than enlightened. My preferred solutions to the “controversy” about null- hypothesis testing are: (1) recognize that we really want to test the hypothesis that an effect is “small,” not null, and (2) use Bayesian methods, which are much more in keeping with the way humans naturally think than are classical statistical methods.

Entertaining diverse assumptions about empirical research, commentators give a wide range of verdicts on the NHSTP defence in Statistical significance. The null-hypothesis significance- test procedure is defended in a framework in which deductive and inductive rules are deployed in theory corroboration in the spirit of Popper's Conjectures and refutations. The defensible hypothetico-deductive structure of the framework is used to make explicit the distinctions between substantive and statistical hypotheses, statistical alternative and conceptual alternative hypotheses, and making statistical decisions and (...) drawing theoretical conclusions. These distinctions make it easier to show that H0 can be true, the effect size is irrelevant to theory corroboration, and “strong” hypotheses make no difference to NHSTP. Reservations about statistical power, meta-analysis, and the Bayesian approach are still warranted. (shrink)

If the NHSTP procedure is essential for controlling for chance, why is there little, if any, discussion of the nature of chance by Chow and other advocates of the procedure. Also, many criticisms that Chow takes to be aimed against the NHSTP procedure are actually directed against the kind of theory that is tested by the procedure.

Several of Krueger & Funder's (K&F's) suggestions may promote more balanced social cognition research, but reconsidered null hypothesis statistical testing (NHST) is not one of them. Although NHST has primarily supported negative conclusions, this is simply because most conclusions have been negative. NHST can support positive, negative, and even balanced conclusions. Better NHST practices would benefit psychology, but would not alter the balance between positive and negative approaches.

Chow's defense of NHSTP ignores the fact that in psychology it is used to test substantive hypotheses in theory-corroborating research. In this role, NHSTP is not only inadequate, but damaging to the progress of psychology as a science. NHSTP does not fulfill the Popperian requirement that theories be tested severely. It also encourages nonspecific predictions and feeble theoretical formulations.

The interpretation of tests of a point null hypothesis against an unspecified alternative is a classical and yet unresolved issue in statistical methodology. This paper approaches the problem from the perspective of Lindley's Paradox: the divergence of Bayesian and frequentist inference in hypothesis tests with large sample size. I contend that the standard approaches in both frameworks fail to resolve the paradox. As an alternative, I suggest the Bayesian Reference Criterion: it targets the predictive performance of the (...) null hypothesis in future experiments; it provides a proper decision-theoretic model for testing a point null hypothesis and it convincingly accounts for Lindley's Paradox. (shrink)

Is there a world beyond the senses? Can we perceive future events before they occur? Is it possible to communicate with others without need of our complex sensory-perceptual apparatus that has evolved over hundreds of millions of years? Can our minds/souls/personalities leave our bodies and operate with all the knowledge and information-processing ability that is normally dependent upon the physical brain? Do our personalities survive physical death?

This commentary advocates an alternative to null-hypothesis testing that was originally represented by Rozeboom over three decades ago yet is not considered by Chow (1996). The central distinguishing feature of this approach is that it allows the scientist to conclude that the data are much better fit by those hypotheses whose values fall inside the interval than by those outside.

The first of 3 objectives in this study was to address the major problem with Null Hypothesis Significance Testing (NHST) and 2 common misconceptions related to NHST that cause confusion for students and researchers. The misconcep- tions are (a) a smaller p indicates a stronger relationship and (b) statistical signifi- cance indicates practical importance. The second objective was to determine how this problem and the misconceptions were treated in 12 recent textbooks used in edu- cation research methods and (...) statistics classes. The third objective was to examine how the textbooks’ presentations relate to current best practices and how much help they provide for students. The results show that almost all of the textbooks fail to acknowledge that there is controversy surrounding NHST. Most of the textbooks dealt, at least minimally, with the alleged misconceptions of interest, but they pro- vided relatively little help for students. (shrink)

In this commentary, I agree with Chow's treatment of null hypothesis significance testing as a noninferential procedure. However, I dispute his reconstruction of the logic of theory corroboration. I also challenge recent criticisms of NHSTP based on power analysis and meta-analysis.

I agree with Gibbs that the message of the base rate literature reads differently depending on which null hypothesis is used to frame the issue. But I argue that the normative null hypothesis, H0: “People use base rates in a Bayesian manner,” is no longer appropriate. I also challenge Adler's distinction between unused and ignored base rates, and criticize Goodie's reluctance to shift research attention to the field. Macchi's arguments about textual ambiguities in traditional base rate (...) problems suggest that empirical testing is needed to tease apart the effects of problem clarification and problem framing. Macdonald's, Fletcher's and Snow's skepticism about the value of Bayesian methods in real world judgment tasks is treated as a challenge for the next generation of empirical base rate studies. (shrink)

I disagree with several of Chow's traditional descriptions and justifications of null hypothesis testing: (1) accepting the null hypothesis whenever p > .05; (2) random sampling from a population; (3) the frequentist interpretation of probability; (4) having the null hypothesis generate both a probability distribution and a complement of the desired conclusion; (5) assuming that researchers must fix their sample size before performing their study.

We argue that Chow's defense of hypothesis-testing procedures attempts to restore an aura of objectivity to the core procedures, allowing these to take on the role of judgment that should be reserved for the researcher. We provide a brief overview of what we call the historical case against hypothesis testing and argue that the latter has led to a constrained and simplified conception of what passes for theory in psychology.

The marker approach is taken as best practice for answering the distribution question: Which animals are conscious? However, the methodology can be used to increase confidence in animals many presume to be unconscious, including C. elegans, leading to a trilemma: accept the worms as conscious; reject the specific markers; or reject the marker methodology for answering the distribution question. I defend the third option and argue that answering the distribution question requires a secure theory of consciousness. Accepting the hypothesis (...) all animals are conscious will promote research leading to secure theory, which is needed to create reliable consciousness tests for animals and AIs. Rather than asking the distribution question, we should shift to the dimensions question: How are animals conscious? (shrink)

Is mental imagery pictorial? In Pylyshyn's view no empirical data provides convincing support to the “pictorial” hypothesis of mental imagery. Phenomenology, Pylyshyn says, is deeply deceiving and offers no explanation of why and how mental imagery occurs. We suggest that Pylyshyn mistakes phenomenology for what it never pretended to be. Phenomenological evidence, if properly considered, shows that mental imagery may indeed be pictorial, though not in the way that mimics visual perception. Moreover, Pylyshyn claims that the “pictorial hypothesis” (...) is flawed because the interpretation of “picture-like” objects in mental imagery takes a homunculus. However, the same point can be objected to Pylyshyn's own conclusion: if imagistic reasoning involves the same mechanisms and the same forms of representation as those that are involved in general reasoning, if they operate on symbol-based representations of the kind recommended by Pylyshyn (1984) and Fodor (1975), don't we need a phenomenological homunculus to tell an imagined bear from the real one? (shrink)

In guarding against inferential mistakes, experimental comparative cognition errs on the side of underattributing sophisticated cognition to animals, or what I refer to as the underattribution bias. I propose eliminating this bias by altering the method of choosing the default, or null, hypothesis. Rather than choosing the most parsimonious null hypothesis, as is current practice, I argue for choosing the best-evidenced hypothesis. Doing so at once preserves the risk-controlling structure of the current statistical paradigm and (...) introduces a sensitivity to probability-conferring empirical and theoretical information. This analysis illustrates how values like parsimony can covertly shape statistical-experimental design and inference. (shrink)

Conventional discussion of research methodology contrast two approaches, the quantitative and the qualitative, presented as collectively exhaustive. But if qualitative is taken as the understanding of lifeworlds, the two approaches between them cover only a tiny fraction of research methodologies; and the quantitative, taken as the routine application to controlled experiments of frequentist statistics by way of the Null Hypothesis Significance Testing Procedure, is seriously flawed. It is contrary to the advice both of Fisher and of Neyman and (...) Pearson, the two sources from which it is drawn. (shrink)

Conventional discussion of research methodology contrast two approaches, the quantitative and the qualitative, presented as collectively exhaustive. But if qualitative is taken as the understanding of lifeworlds, the two approaches between them cover only a tiny fraction of research methodologies; and the quantitative, taken as the routine application to controlled experiments of frequentist statistics by way of the Null Hypothesis Significance Testing Procedure, is seriously flawed. It is contrary to the advice both of Fisher and of Neyman and (...) Pearson, the two sources from which it is drawn. (shrink)

Recent work in the physics literature demonstrates that, in particular classes of rotating spacetimes, physical light rays in general do not traverse null geodesics. Having presented this result, we discuss its philosophical significance, both for the clock hypothesis, and for the operational meaning of the metric field.

The target article advanced the null, unified and widely misinterpreted generative hypothesis regarding second language (L2) acquisition. Postulating that UG (Universal Grammar) constrains L2 knowledge growth does not entail identical developmental trajectories for L2 and first language (LI) acquisition; nor does it preclude a role for the L1. In embracing this hypothesis, we maintain a distinction between competence and performance. Those who conflate the two repeat fundamental and by no means unprecedented misconstruals of the generative enterprise, and (...) more specifically, of the empirical content of the null hypothesis regarding L2 linguistic knowledge growth. We hope to have identified certain common goals, the adoption of which might constitute a firm foundation for continued productive interdisciplinary development of contemporary theoretical and experimental L2 acquisition research. (shrink)

Recent work in the physics literature demonstrates that, in particular classes of rotating spacetimes, physical light rays in general do not traverse null geodesics. Having presented this result, we discuss its philosophical significance, both for the clock hypothesis (and, in particular, a recent purported proof thereof for light clocks), and for the operational meaning of the metric field. 1Introduction 2Fletcher's Theorem 2.1Maudlin on the clock hypothesis in special relativity 2.2Fletcher’s result in special relativity 2.3Fletcher’s theorem in general (...) relativity 3Electromagnetism and the Geometrical-Optical Limit 3.1Maxwell’s equations in curved spacetime 3.2The geometrical-optical limit 3.3Rotating spacetimes 3.4Aren’t Gödel spacetimes unphysical? 4The Clock Hypothesis and Chronogeometry 4.1Natural and mathematical observations 4.2Clock registry discord 4.3Chronogeometry 5Conclusion. (shrink)

Chow's defense of the null-hypothesis significance- test procedure is thoughtful and compelling in many respects. Nevertheless, techniques such as meta-analysis, power analysis, effect size estimation, and confidence intervals can be useful supplements to NHSTP in furthering the cumulative nature of behavioral research, as illustrated by the history of research on the spontaneous recovery of verbal learning.

(2011). Korn and Freidlin's Misunderstanding of the Null Hypothesis Significance Testing Procedure. The American Journal of Bioethics: Vol. 11, No. 3, pp. 15-16.

A common strategy in comparative cognition is to require that one reject associative learning as an explanation for behavior before concluding that an organism is capable of causal reasoning. In this paper, I argue that standard causal-reasoning tasks can be explained by a powerful form of associative learning: unlimited associative learning (UAL). The lesson, however, is not that researchers should conduct more studies to reject UAL, but that they should instead focus on 1) enriching the cognitive hypothesis space and (...) 2) testing a broader range of information processing patterns—errors, biases and limits, rather than successful problem solving alone. (shrink)

Reexamining William Rozeboom’s recommendations for the future direction of disciplines such as psychology and philosophy is imminent due to the pressing issues in null hypothesis significance testing. An overreliance on NHST forms the basis of the replication crisis in psychology. Likewise, the discipline’s stringent guidelines on significance levels convey a pressure to publish, which is also significantly contributing to the replication crisis. As researchers’ careers are staked on the extent to which they publish, reassessing the fundamental issues with (...) NHST within the context of Rozeboom’s ideas is paramount. In this brief review, I focus specifically on Rozeboom’s critiques of NHST and on a proposed alternative for evaluating the depth of findings within the framework of theoretical psychology. Thereafter, I compare his foreboding concerns with modern issues facing the validity of psychology and posit Rozeboom prophesized the failings of the discipline years ahead of his time. Keywords: Theoretical Psychology; NHST; William Rozeboom; P-Hacking; Explanatory Induction. (shrink)

The soundness of Chow's (1996; 1998a) argument depends on the soundness of his assertion that statistical significance may be understood to signify that chance may be excluded as the reason for results. The examples and arguments provided here show that statistical significance signifies no such thing.

In this article I give a critical evaluation of the use and limitations of null-model-based hypothesis testing as a research strategy in the biological sciences. According to this strategy, the null model based on a randomization procedure provides an appropriate null hypothesis stating that the existence of a pattern is the result of random processes or can be expected by chance alone, and proponents of other hypotheses should first try to reject this null (...) class='Hi'>hypothesis in order to demonstrate their own hypotheses. Using as an example the controversy over the use of null hypotheses and null models in species co-occurrence studies, I argue that null-model-based hypothesis testing fails to work as a proper analog to traditional statistical null-hypothesis testing as used in well-controlled experimental research, and that the random process hypothesis should not be privileged as a null hypothesis. Instead, the possible use of the null model resides in its role of providing a way to challenge scientists’ commonsense judgments about how a seemingly unusual pattern could have come to be. Despite this possible use, null-model-based hypothesis testing still carries certain limitations, and it should not be regarded as an obligation for biologists who are interested in explaining patterns in nature to first conduct such a test before pursuing their own hypotheses. (shrink)

Montalbetti (1984) points out certain semantic differences between phonetically full and phonetically empty pronouns (henceforth full and n u l l pronouns) that challenge the traditional interpretive parallelism between empty and full categories (see Chomsky 1981, 1982). He shows that both in subject (1) and object position (2), while null pronouns can be interpreted as bound variables (as in (1a) and (2a) ), full pronouns cannot (as in (1c) and (2c)).

We evaluate a common reasoning strategy used in community ecology and comparative psychology for selecting between competing hypotheses. This strategy labels one hypothesis as a “null” on the grounds of its simplicity and epistemically privileges it as accepted until rejected. We argue that this strategy is unjustified. The asymmetrical treatment of statistical null hypotheses is justified through the experimental and mathematical contexts in which they are used, but these contexts are missing in the case of the “pseudo- (...) class='Hi'>null hypotheses” found in our case studies. Moreover, statistical nulls are often not epistemically privileged in practice over their alternatives because failing to reject the null is usually a negative result about the alternative, experimental hypothesis. Scientists should eschew the appeal to pseudo-nulls. It is a rhetorical strategy that glosses over a commitment to valuing simplicity over other epistemic virtues in the name of good scientific and statistical methodology. (shrink)

Neyman-Pearson methods in statistics distinguish between Type I and Type II errors. Through rigid control of Type I error, the "null" hypothesis typically receives the benefit of the doubt. I compare philosophers' interpretations of this feature of Neyman-Pearson tests with interpretations given in statistics textbooks. The pragmatic view of the tests advocated by Neyman, largely rejected by philosophers, lives on in many textbooks. Birnbaum thought the pragmatic view has a useful "heuristic" role in understanding testing. I suggest that (...) it may have the opposite effect. (shrink)

The meaning of an experimental result depends on the experiment's conceptual backdrop, particularly its null hypothesis. This observation provides the basis for a functional interpretation of belief in the base rate fallacy. On this interpretation, if the base rate fallacy is to be labelled a “myth,” then it should be recognized that this label is not necessarily a disparaging one.