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Course Criteria
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3.00 Credits
Mendelian genetic traits. Population genetics; Hardy-Weinberg, allelic variation, subdivision. Likelihood inference, information and power; latent variables and EM algorithm. Pedigree relationships and gene identity. Meiosis and recombination. Linkage detection. Multipoint linkage analysis. Offered: jointly with STAT 550; A.
Prerequisite:
STAT 390 and STAT 394, or permission of instructor
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3.00 Credits
Monks Statistical basis for describing variation in quantitative traits. Decomposition of trait variation into components representing genes, environment and gene-environment interaction. Methods of mapping and characterizing quantitative trait loci. Offered: jointly with STAT 551; W.
Prerequisite:
STAT/ BIOST 550; STAT 423 or BIOST 515; or permission of instructor
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3.00 Credits
Wijsman Overview of probability models, inheritance models, penetrance. Association and linkage. The lod score method. Affected sib method. Fitting complex inheritance models. Design mapping studies; multipoint, disequilibrium, and fine-scale mapping. Ascertainment. Offered: jointly with STAT 552; Sp.
Prerequisite:
STAT/BIOST 551; GENET 371; or permission of instructor
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3.00 Credits
Generalized linear models, REML in mixed models for randomized blocks, split plots, longitudinal data. Generalized estimating equations, empirical model building, cross validation, recursive partitioning, generalized additive models, projection pursuit. Offered: jointly with STAT 570.
Prerequisite:
STAT 512, 513; BIOST/STAT 533 or STAT 421 and STAT 423, and a course in matrix algebra
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3.00 Credits
Generalized linear models, REML in mixed models for randomized blocks, split plots, longitudinal data. Generalized estimating equations, empirical model building, cross validation, recursive partitioning, generalized additive models, projection pursuit. Offered: jointly with STAT 571.
Prerequisite:
BIOST 570
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3.00 Credits
Generalized linear models, REML in mixed models for randomized blocks, split plots, longitudinal data. Generalized estimating equations, empirical model building, cross validation, recursive partitioning, generalized additive models, projection pursuit. Offered: jointly with STAT 572.
Prerequisite:
BIOST 571
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3.00 Credits
Advanced topics in generalized linear models and the analysis of categorical data: overdispersion, quasilikelihood, parameters in link and variance functions, exact conditional inference, random effects, saddlepoint approximations. Credit/no credit only. Offered: jointly with STAT 573; alternate years; Sp.
Prerequisite:
BIOST 571 and STAT 582
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3.00 Credits
Use of multivariate normal sampling theory, linear transformations of random variables, one- and two-sample tests, profile analysis, partial and multiple correlation, multivariate ANOVA and least squares, discriminant analysis, principal components, factor analysis, robustness, and some special topics. Some computer use included. Offered: jointly with STAT 574; alternate years.
Prerequisite:
BIOST 570 or permission of instructor
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3.00 Credits
Statistical methods for censored survival data arising from follow-up studies on human or animal populations. Parametric and nonparametric methods, Kaplan-Meier survival curve estimator, comparison of survival curves, logrank test, regression models including the Cox proportional hazards model, competing risks. Offered: jointly with STAT 576.
Prerequisite:
STAT 581 and either BIOST 515, STAT 473, or equivalent
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3.00 Credits
Concepts important in experimental design: randomization, blocking, confounding. Application and analysis of data from randomized blocks designs, Latin and Graeco-Latin squares, incomplete blocks designs, split-plot and repeated measures, factorial and fractional replicates, response surface experiments. 0) or permission of instructor. Offered: jointly with STAT 577.
Prerequisite:
BIOST 570 or STAT 421 (minimum 3
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