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When subjects are measured twice, once at each of two symmetrical locations or times, stability of responses in the absence of treatment within subjects, together with comparability of untreated responses between subjects, is often viewed as supporting a conclusion that differences between treated and control responses reflect effects actually caused by the treatment. The degree to which this intuitive argument is formally correct is explored is several related models: a multivariate Normal model, a nonparametric model defined by symmetries, an analogues randomized experiment, and sensitivity analysis model for observational studies in which treatments are not randomly assigned to subjects, nor to locations within subjects. Card and Kreuger's study of the employment effects of the minimum wage is used to illustrate the methods. [ABSTRACT FROM AUTHOR]

The article presents information about Samuel S. Wilks, a great contributor to statistics. Wilks' behavior toward applications was peculiarly split, he encouraged his students to work on applications, not always an easy thing to do in a strongly theoretical mathematics department; he often told students about applications that he regarded as "neat" or "cute" or "clever"; the statistical colloquium he guided often had speakers on practical applications of mathematical statistics; he himself wrote some practical papers in statistics, but in the classroom he rarely discussed applications. Repeatedly, however, practical problems explicitly influenced both his own publications and those of his students and Wilks often used applications as motivation for the discussion of distribution theory, usually going well beyond the needs of the original problem. The papers to be discussed exhibit incompletely and fragmentarily a major influence on the work of the man and his students. Wilks watched the development of the statistical theory of order statistics closely. Indeed he wrote a masterful summary of the literature. The general area involves the study of the statistical properties of ordered measurements.