BIST-512 Categorical Data Analysis
Spring for 2017-2018
Faculty:
Textbook: An Introduction to Categorical Data Analysis by Alan Agresti; ISBN: 0471113387
Credits: 3
Prerequisites: Introductory Statistics: confidence interval, hypothesis testing; BIST-511

Sections:

BIST-512-01 Categorical Data Analysis
Spring for 2017-2018
Faculty:
3 modules: regression and ANOVA, generalized linear models, longitudinal models.
Lab teaches SAS procedures to fit these models.
Regression and ANOVA : fitting a linear regression, least squares method, regression in observational studies, estimation and prediction of Y for a given X, predicted sample mean of Y, testing large deviation, no intercept model, correlation coefficient, bivariate normal distribution, testing single correlation, comparing correlations, rank correlation, 2×C contingency tables, linear trend, R×C contingency tables, fixed-effect ANOVA, model notation, F-test, planned comparisons, orthogonal comparisons, random effects model, homogeneity of variance, randomized blocks, latin squares.
Generalized Linear Models : exponential family, proportion, count and rate data, link functions, estimation, logistic and Poisson regressions, fixed and random effects, repeated measures, model selection.
Longitudinal Models: generalized estimating equations, estimation, clustered data, linear mixed models, model fit.

Textbook: Applied Linear Statistical Models with Student CD, 5th Edition, by Kutner, Nachtsheim, Neter and Li, McGraw-Hill Higher Education, 2005
ISBN: 9780073108742
Credits: 3
Prerequisites: Introductory Statistics: confidence interval, hypothesis testing; BIST-511
More information
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