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Course Criteria
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3.00 Credits
Prerequisite: PHST 781 "Advanced Linear Models" or permission of instructor. The course focuses on theory and application of linear and nonlinear mixed effect models, particularily, the application of mixed models to longitudinal data analyses.
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3.00 Credits
Prerequisite: PHST 681 or permission of instructor. Restricted to PHDA and PHCI majors. This course will cover modern/classical statistical/biostatistical methods like smoothing techniques and data summaries, linear models, generalized linear models, modern nonlinear regression techniques, multivariate statistics using S-PLUS/R and SAS.Several real data examples will be analyzed following the 4th edition of the book titled Modern Applied Statistics with S by Venables and Ripley.
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3.00 Credits
Prerequisite: PHST 622, 710, 781 or permission of instructor. Restricted to PHDA, PHCI and PHMPH majors. The course covers advanced topics in statistical computing, with an emphasis on biostatistical applications. Topics include matrix factorization, methods, numerical optimization, the EM algorithm, random number generation, Monte Carlo techniques, simulation, radomization an resampling methods, bootstrapping, and recursivepartitioning. Computer programming will be conducted using MATLAB,R, and SAS IML.
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3.00 Credits
Prerequisite: PHCI 624, PHST 684, 726, or permission of instructor. Restricted to PHDA, PHCI and PHMPH majors. Advanced statistical methods for design and analysis of clinical trials. Content includes analysis of complex clinical trial designs, including post-stratification, cross-over, phases I, II. and III clinical trials. Sample size calculations will be covered. Interim analysis methods and sample size re-estimation methods will be developed.
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3.00 Credits
Prerequisite: PHST 681 or permission of instructror. Restricted to PHDA, PHCI and PHMPH majors. The course introduces experimental design principles and covers specific designs in detail.Topics include the completely randomzed design, the randomized complete block design, cross-over designs, nested and hierarchical designs, factorial treatment arrangements, incomplete block designs, response surface methodology, and optimal designs. Concepts will be illustrated using examples from the health services.
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1.00 Credits
Prerequisite: PHST 681 or permission of instructor. Restricted to PHDA, PHCI and PHMPH majors. Co-requisites: PHCI 624. Statistical methods laboratory to accompany PHCI 624: Clinical Trials I, a.k.a. Design of Clinical Trials. Statistical methods described in Clinical Trials I will be demonstrated and taught with hands-on examples and homework problems. Methods covered include randomization methods, sample size calculations, post-stratification, Phase II early-stopping designs, repeated -measures analysis, survival analysis, and methods to avoid or reduce multiplicity.
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3.00 Credits
Prerequisite: PHST 662 or consent of instructor. Restricted to PHDA and PHCI majors. This course is a mathematically sophisticated introduction to the theory and methods of statistical inference. Students will learn fundamental technical tools that are essential to carry out methodological research in the field of Biostatistics. Emphasis will be placed on how to correctly propose statistical methods in a general setting including concepts such as asymptotic unbiasedness, robust variance estimation and efficiency.
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3.00 Credits
Prerequisite: Admission to Biostatistics doctoral concentration or consent of instructor. A mathematically advanced introduction to theory and methods of nonparametric statistical methods.Course will be useful to students planning to analyze data that do not follow a standard parametric distribution.
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3.00 Credits
Prerequisite: PHST 662, 680 or consent of instructor. Restricted to PHDA and PHCI majors. An introduction to the theory of linear models, with an emphasis on health sciences applications. Topic coverage includes projections, distributions of quadratic forms under normality, estimation procedures, general linear hypotheses, estimating and testinglinear parametric functions, simultaneous inference, multifactor ANOVA models, hierarchical linear models, mixed effects models, and covariance parameter estimation methods. Examples will be illustrated using advanced statistical software.
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3.00 Credits
Prerequisite: PHST 662, 681, 781 (may be taken concurrently) or consent of instructor. Restricted to PHDA, PHCI and PHMPH majors. Advanced statistical methods using inference based on the exponential family of distributions. Relationship to linear and non-linear regression. Theoretical development of link functions. Model-building and assessment of goodness-of-fit. Estimation and hypothesis testing. Correlated resonse methods using generalized estimating equations.
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