In support of null hypothesis significance testing

Many criticisms have been levelled at null hypothesis significance testing (NHST). It is argued here that although there is reason to doubt that data subjected only to NHST have been subjected to sufficient analysis, the search for clear answers to well-formulated questions derived from substantive hypotheses is well served by NHST. To reliably draw inferences from data, however, NHST may need to be complemented by additional methods of analysis, such as the use of confidence intervals and of estimates of the degree of association between independent and dependent variables. It is argued that these should be seen as complements of, rather than as substitutes for, NHST since they do not directly test the strength of evidence against a null hypothesis.     

Mass-dependent mass loss: how to get the null hypothesis wrong

In ecological studies there is often considerable interest in the question whether the magnitude of mass loss in animals depends on their initial mass. Cichon et al. have recently questioned the validity of conventional statistical testing of relations between mass loss and initial mass, and derived a new null hypothesis to be used for a "correct" statistical analysis. Here, I demonstrate that the method employed by Cichon et al. is wrong and leads to false conclusions. Hence, there is no need to reverse the biological interpretation of previously published results.     

Anthropomorphism,primatomorphism, mammalomorphism: understanding cross-species comparisons

The charge that anthropomorphizing nonhuman animals is a fallacy is itself largely misguided and mythic. Anthropomorphism in the study of animal behavior is placed in its original, theological context. Having set the historical stage, I then discuss its relationship to a number of other, related issues: the role of anecdotal evidence, the taxonomy of related anthropomorphic claims, its relationship to the attribution of psychological states in general, and the nature of the charge of anthropomorphism as a categorical claim. I then argue that the categorical reading of anthropomorphism cannot work and that it misrepresents what is being claimed when one claims that traits are shared between humans and nonhumans. We should think of such claims not as anthropomorphic per se– because that implies the trait is intrinsically human and only derivatively nonhuman. Instead, traits shared with mammals are mammalomorphic, for example, or primatomorphic when shared by primates.     

A new null hypothesis for measuring the degree of plant community organization

An attempt is made to derive a measure for the degree of plant community organization, which would not be based on species co-occurrence and co-abundance. The use of the independent random distribution hypothesis (IRDH) is suggested for this purpose. The hypothesis is expected to be valid, if no deterministic phytosociological-structure-generating mechanism is present. If structural variability is used as a statistic for testing the hypothesis, deviances from the conditions of IRDH (species distributions are independent from each other, environmental gradients are lacking) will be attributable either to species interactions (smaller structural variability than expected), or to environmental heterogeneity (greater structural variability than expected). Structural variability is evaluated as the variance of species diversity, the indexN=exp(H') is used for measuring diversity. The precise measure of the degree of community organizationW is computed as the shift between two empirical distributions:D ^* (VN) or Bootstrap distribution of variance of diversity in the community, andD ^o (VN) or the random community variability distribution, which is evaluated after simulating the IRDH conditions.A satisfactory interpretation can be given to the results of evaluatingW for 11 data sets of 10 relevés each.Abbreviation IRDH Independent random distribution hypothesis     

Inherent bias toward the null hypothesis in conventional multipoint nonparametric linkage analysis

Traditional nonparametric "multipoint" statistical procedures have been developed for assigning allele-sharing values at a locus of interest to pairs of relatives for linkage studies. These procedures attempt to accommodate a lack of informativity, nongenotyped loci, missing data, and related issues concerning the genetic markers used in a linkage study. However, such procedures often cannot overcome these phenomena in compelling ways and, as a result, assign relevant relative pairs allele-sharing values that are "expected" for those pairs. The practice of assigning expected allele-sharing values to relative pairs in the face of a lack of explicit allele-transmission information can bias traditional nonparametric linkage test statistics toward the null hypothesis of no locus effect. This bias is due to the use of expected values, rather than to a lack of information about actual allele sharing at relevant marker loci. The bias will vary from study to study on the basis of the DNA markers, sample size, relative-pair types, and pedigree structures used, but it can be extremely pronounced and could contribute to a lack of consistent success in the application of traditional nonparametric linkage analyses to complex human traits and diseases. There are several potential ways to overcome this problem, but their foundations deserve greater research. We expose many of the issues concerning allele sharing with data from a large affected-sibling-pair study investigating the genetic basis of autism.     

Anthropomorphism and 'mental welfare' of fishes

Anthropomorphism, the use of human characteristics as a foundation for interpreting behavior and mental capacities of animals, is a bias undermining our understanding of other species, especially species as evolutionarily distant from humans as fishes. Anthropomorphism is not justified by allusions to evolutionary continuity among vertebrates, because no living vertebrate was ever a descendant of humans, so none could have inherited human traits. Nonetheless, it has recently been claimed that fishes are capable of conscious experiences of pain and emotional feelings and that mental welfare is an important issue for fishes. This paper shows that the evidence supporting claims for experiences of pain or conscious emotions by fishes is conceptually and methodologically flawed. In addition, the paper shows that the natural history and behavior of diverse fish species is inconsistent with a presumption of human-like awareness. This behavioral evidence is in accord with neurobiological observations showing that fishes are very different from us and are unlikely to have a capacity for awareness of pain or emotional feelings that meaningfully resemble our own. The factors that are detrimental to fish welfare have been well delineated by valid, objective indicators of physiological and behavioral well-being. This knowledge should guide welfare decisions. An empirical and non-anthropomorphic examination of diverse fishes and their adaptations should be the foundation for welfare decisions that would be truly beneficial to fishes and humans alike.     

Bias toward the null hypothesis in model-free linkage analysis is highly dependent on the test statistic used

Recently, it has been suggested that traditional nonparametric multipoint-linkage procedures can show a "bias" toward the null hypothesis of no effect when there is incomplete information about allele sharing at genotyped marker loci (or at positions in between marker loci). Here, I investigate the extent of this bias for a variety of test statistics commonly used in qualitative- ("affecteds only") and quantitative-trait linkage analysis. Through simulation and analytical derivation, I show that many of the test statistics available in standard linkage analysis packages (such as Genehunter, Merlin, and Allegro) are, in fact, not affected by this bias problem. A few test statistics--most notably the nonparametric linkage statistic and, to a lesser extent, the Aspex-MLS and Haseman-Elston statistics--are affected by the bias. Variance-components procedures, although unbiased, can show inflation or deflation of the test statistic attributable to the inclusion of pairs with incomplete identity-by-descent information. Results obtained--for instance, in genome scans--using these methods might therefore be worth revisiting to see if greater power can be obtained by use of an alternative statistic or by eliminating or downweighting uninformative relative pairs.     

Thinking with Animals: New Perspectives on Anthropomorphism

Thinking with Animals: New Perspectives on Anthropomorphism. Lorraine Daston and Gregg Mitman, eds. New York: Columbia University Press, 2005. 230 pp.