A General Approach to Hypothesis Testing for Nonparametric Tests

Researchers have preferred normal-theory tests over nonparametric procedures, despite evidence that the statistical properties of the latter are sometimes superior for variables and subject populations frequently encountered in educational and psychological research. Two ongoing concerns among researchers are that non-parametric tests exist only in simple cases (e.g., univariate one-, two-, and J-sample tests) and that these tests are often not available in statistical computing programs. The nonparametric hypothesis-testing model of Puri and Sen (1969, 1985) circumvents these concerns by permitting a variety of statistical hypotheses to be tested using existing computing programs. The breadth and flexibility of this model is illustrated with several examples.