Measures of agreement, Measures of association, Consensus indices,

It is generally acknowledged that humans display highly variable sensitivity to pain, including variable responses to identical injuries or pathologies. The possible contribution of genetic factors has, however, been largely overlooked. An emerging rodent literature documents the importance of genotype in mediating basal nociceptive sensitivity, in establishing a predisposition to neuropathic pain following neural injury, and in determining sensitivity to pharmacological agents and endogenous antinociception. One clear finding from these studies is that the effect of genotype is at least partially specific to the nociceptive assay being considered. In this report we begin to systematically describe and characterize genetic variability of nociception in a mammalian species, Mus musculus. We tested 11 readily-available inbred mouse strains (129/J, A/J, AKR/J, BALB/cJ, C3H/HeJ, C57BL/6J, C58/J, CBA/J, DBA/2J, RIIIS/J and SM/J) using 12 common measures of nociception. These included assays for thermal nociception (hot plate, Hargreaves' test, tail withdrawal), mechanical nociception (von Frey filaments), chemical nociception (abdominal constriction, carrageenan, formalin), and neuropathic pain (autotomy, Chung model peripheral nerve injury). We demonstrate the existence of clear strain differences in each assay, with 1.2 to 54-fold ranges of sensitivity. All nociceptive assays display moderate-to-high heritability (h2 = 0.30-0.76) and mediation by a limited number of apparent genetic loci. Data comparing inbred strains have considerable utility as a tool for understanding the genetics of nociception, and a particular relevance to transgenic studies.

The quadratic assignment paradigm developed in operations research is discussed as a general approach to data analysis tasks characterized by the use of proximity matrices. Data analysis problems are first classified as being either static or non-static. The term 'static' implies the evaluation of a detailed substantive hypothesis that is posited without the aid of the actual data. Alternatively, the term 'non-static' suggests a search for a particular type of relational structure within the obtained proximity matrix and without the statement of a specific conjecture beforehand. Although the static class of problems is directly related to several inference procedures commonly used in classical statistics, the major emphasis in this paper is on applying a general computational heuristic to attack the non-static problem and in using the quadratic assignment orientation to discuss a variety of research tactics of importance in the behavioral sciences and, particularly, in psychology. An extensive set of numerical examples is given illustrating the application of the search procedure to hierarchical clustering, the identification of homogeneous object subsets, linear and circular seriation, and a discrete version of multidimensional scaling. CONTENTSAbstract .

We discuss the task of evaluating conjectures of order within proximity matrices in connection with an inappropriate inference procedure proposed by Wakeneld and Doughtie and subsequently adopted by other authors. This strategy is criticized and a different method based on randomization is proposed. An example from Holland's theory of personality types is used throughout this article for illustration. Finally, we develop the testing of two competing theoretical conjectures against a given proximity matrix as a natural extension of evaluating one such hypothesis.

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