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Course Criteria
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4.00 Credits
Analysis of categorical data including two sample methods, sets of 2 x 2 tables, R x C tables, and logistic regression. Classification and discrimination techniques. Survival analysis including product limit estimates and the Cox proportional hazards model. Offered: Sp.
Prerequisite:
BIOST 512 or permission of instructor
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4.00 Credits
Mathematically sophisticated presentation of principles and methods of data description; graphics; point, confidence interval estimation; hypothesis testing; relative risk; odds ratio; Mantel-Haenszel; chi-square test (matrix algebra required). Examples drawn from biomedical literature; realdata sets analyzed using statistical computer packages. Offered: A.
Prerequisite:
biostatistics majors or permission of instructor
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4.00 Credits
Mathematically sophisticated introduction to linear models; multiple regression, correlation; residual analysis; dummy variables; analysis of covariance; one-, two-way analysis of variance; randomized blocks; fixed, random effects (repeated measure, factorial designs); multiple comparisons (matrix algebra required). Real biomedical data sets analyzed. Offered: W.
Prerequisite:
BIOST 514, biostatistics major, or permission of instructor
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3.00 Credits
Theory and application of statistical techniques used in genetic epidemiology. Includes discussion of association studies, linkages and segregation analyses. Examples stressed with reference to assumptions and limitations. Offered: jointly with EPI 516/PHG 519.
Prerequisite:
either BIOST 513 or BIOST 518; PHG 511/EPI 517, or permission of instructor
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4.00 Credits
Introduction to the analysis of biomedical data. Descriptive and inferential statistical analysis for discrete, continuous, and right censored random variables. Analytic methods based on elementary parametric and non-parametric models for one sample; two sample (independent and paired), stratified sample, and simple regression problems. Offered: A.
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4.00 Credits
Multiple regression for continuous, discrete, and right censored response variables, including dummy variables, transformations, and interactions. Introduction to regression with correlated outcome data. Model and case diagnostics. Computer assignments using real data and standard statistical computer packages. Offered: W.
Prerequisite:
BIOST 517 or permission of instructor
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3.00 Credits
Davis Introduces advanced methodologic methods, including recursive partitioning, developing clinical prediction rules, analyses of community-level associations or interventions, case-crossover and case-only designs, propensity scores, two-stage sampling, and missing data imputation. Offered: jointly with EPI 515. A.
Prerequisite:
EPI 512; EPI 513
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4.00 Credits
Statistical aspects of design, data analytic models appropriate to classes of experiments most commonly employed in biomedical sciences. One-, two-way analyses of variance; factorial, crossed, nested, repeated measures designs. Clean, messy real-data sets analyzed using standard statistical computer packages. Offered: alternate years; Sp.
Prerequisite:
either BIOST 511 and BIOST 512, or BIOST 517 and BIOST 518, or equivalent
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4.00 Credits
No course description available.
Prerequisite:
Separate File
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3.00 Credits
Design of medical studies, with emphasis on randomized controlled clinical trials. Bias elimination, controls, treatment assignment and randomization, precision, replication, power and sample size calculations, stratification, and ethics. Suitable for graduate students in biostatistics and for research-oriented graduate students in other scientific fields. Offered: jointly with STAT 524; Sp.
Prerequisite:
BIOST 511 or equivalent, and one of BIOST 513, BIOST 518, STAT 421, STAT 423, STAT 512, or EPI 512; or permission of instructor
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