Design and analysis of Phase I-III clinical trials, interim monitoring of trials, sample size, power, crossover trials, bioequivalency, mixed models, and meta analysis.

Multinomial and product-multinomial models; large-sample theory of estimation and testing, Pearson chi-square and modified chi-square statistics, Pearson-Fisher Theorem, Wald Statistics and generalized least squares technique; applications to problems of symmetry, association and hypotheses of no interaction in multi-dimensional contingency tables.

Survey of multivariate statistical techniques important in applied research. Focus on multivariate structure-seeking methods, but attention given to important hypothesis testing applications in ANOVA and MANOVA. Emphasis on implementation using modern statistical software and interpretation of results in context.

Measures on the real line and probability spaces, Lebesque measure, properties of distribution functions and random variables, integrals and expectations.

UMP and UMP unbiased tests for multiparametric exponential families; locally best tests; invariance and permutation tests, UMP invariant tests for linear hypotheses; asymptotic aspects of classical statistics, ML estimation and concepts of efficiency; sequential probability ratio test; confidence set, UMA unbiased and invariance confidence sets.

Half-time to full-time work on thesis. May be repeated to a maximum of six semesters.

Half-time to full-time work on dissertation. May be repeated to a maximum of six semesters.

Residency credit for dissertation research after the qualifying examination. Students may register for this course in the semester of the qualifying examination. A minimum of two semesters are required as well as continuous enrollment (Fall and Spring) until the dissertation is completed and defended.

May be repeated to a maximum of 12 hours.

May be repeated indefinitely.