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 |
PUBH
6400. Topics: Biostatistics.
|
(1.0-4.0 cr; prereq # )
|
Topics of interest in biostatistics.
|
Effective: Fall 2005
|
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PUBH 6414.
Biostatistical Methods I.
|
(3.0 cr; prereq =6450; Public Health [MPH
or certificate] student or [environmental health [MS or PhD]
or health journalism MA or health informatics [MS or PhD]] major
or #)
|
Descriptive statistics, graphical methods.
Use of Excel. Proportions, relative risk, odds ratios. Random
sampling. Estimates of mean, medians, measures of variability.
Normal distribution, t-/chi-square tests. Confidence intervals.
Correlation/regression. Inference/causality.
|
Effective: Fall 2005
|
PUBH 6415.
Biostatistical Methods II.
|
(3.0 cr; prereq PubH 6414, [public health
[MPH or certificate] student or environmental health [MS or
PhD] or health journalism MA or health informatics [MS or PhD]]
major] or #)
| Statistical computing using SAS. Multiple regression. Data transformations. Relative risk, odds ratio estimation. Logistic regression. Survival analysis. Kaplan-Meier tables, survival curves.
|
Effective: Fall 2005
|
PUBH 6420.
Introduction to SAS Programming.
| (1.0 cr; prereq Health sciences grad student or #)
| Use of SAS for analysis of biomedical data. Data manipulation/description. Basic statistical analyses (t-tests, chi-square, simple regression).
| Effective: Fall 2002
|
PUBH 6450.
Biostatistics I.
| (4.0 cr; prereq [Math 1031, health science grad student] or #)
| Descriptive statistics. Gaussian probability models, point/interval estimation for means/proportions. Hypothesis testing, including t, chi-square, and nonparametric tests. Simple regression/correlation. ANOVA. Health science applications using output from statistical packages.
|
Effective: Fall 2005
|
PUBH 6451.
Biostatistics II.
|
(4.0 cr; prereq [6450, competence in SAS
through 6420] or equiv or grade of at least B in [6414, 6415])
| Two-way ANOVA, interactions, repeated measures, general linear models. Logistic regression for cohort and case-control studies. Loglinear models, contingency tables, Poisson regression, survival data, Kaplan-Meier methods, proportional hazards models.
|
Effective: Fall 2005
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PUBH 6460.
Introduction to Biostatistical Thinking.
| (1.0 cr; prereq Biostatistics major or #; S-N only)
| Aspects of Biostatistics as practiced at U of M and as described in research literature.
|
Effective: Fall 2005
|
PUBH6470.
SAS Procedures and Data Anlaysis
|
(3 cr; prereq
|
|
Effective: Fall 2005
|
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PUBH 7400.
Topics: Biostatistics.
|
(1.0-4.0 cr; prereq # )
|
Topics of interest in biostatistics.
|
Effective: Fall 2005
|
PUBH 7405.
Biostatistics: Regression.
|
(4.0 cr; prereq =6450, =6451; [[Stat 5101
or &Stat 5101], biostats major] or #)
|
T-tests, confidence intervals, power,
type I/II errors. Exploratory data analysis. Simple linear regression,
regression in matrix notation, multiple regression, diagnostics.
Ordinary least squares, violations, generalized least squares,
nonlinear least squares regression. Introduction to General
linear Model. SAS and S-Plus used.
|
Effective: Fall 2005
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PUBH 7406.
Biostatistics: ANOVA and Design.
|
(4.0 cr; prereq 7405, [STAT 5102 or concurrent
enrollment in STAT 5102], Biostatistics major] or #
| Single factor ANOVA, diagnostics, classical non-parametrics, multifactor ANOVA, multiple comparisons, power and sample size determination, calculating expected mean squares, random/mixed effects models. ANOVA in regression notation. Randomized block designs, nested designs, repeated measures designs, cross-over designs. SAS and S-Plus used.
|
Effective: Fall 2005
|
PUBH 7407.
Analysis of Categorical Data.
|
(3.0 cr; prereq PubH 7405 and [Stat 5102
or concurrent enrollment in Stat 5102]
| Contingency tables, odds ratio, relative risk, chi-square tests, log-linear models, logistic regression, conditional logistic regression, Poisson regression, matching, generalized linear models for independent data. SAS/S-Plus used throughout.
|
Effective: Fall 2005
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PUBH
7420. Clinical Trials: Design, Implementation, and Analysis.
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(3.0 cr; prereq 6451 or 7406 or
#)
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Introduction to and methodology
of randomized clinical trials: design issues, sample size,
operational details, interim monitoring, data analysis
issues, and overviews.
|
Effective: Fall 2005
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PUBH 7430.
Statistical Methods for Correlated Data.
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(3.0 cr; prereq [[6420 or equiv], [6451
or 7406or Stat 5303 or equiv], familiarity with matrix notation]
or #)
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Correlated data arising from data collected
over time or space, group randomizations, cluster sampling,
nested designs, or random effects assumptions. Modeling, analysis,
and interpretation appropriate for such data, for normally or
non-normally (e.g. binary, Poisson, gamma) distributed outcomes.
Computing using SAS software.
|
Effective: Fall 2005
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PUBH 7435.
Latent Variable Models.
|
(3.0 cr; prereq [6414,65415] or [6450,
6452] or #)
|
Introduction to use of statistical techniques
known collectively as latent variable models. Exploratory/confirmatory
factor analysis, path analysis, structural equation modeling,
latent trait models, latent class models. SAS/AMOS software
are used.
|
Effective: Fall 2005
|
| PUBH 7440.
Introduction to Bayesian Analysis. |
(3.0 cr; prereq [[[7405, 7406] or [Stat
5101, Stat 5102] or equiv], [[Public health MPH or biostatistics
or statistics] grad student]] or #)
|
| Introduction to Bayesian methods. Comparison
with traditional frequentist methods. Emphasizes data analysis
via modern computing methods: Gibbs sampler, WinBUGS software
package. |
Effective: Fall 2005
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PUBH 7445.
Statistics for Human Genetics and Molecular Biology.
|
(3.0 cr; prereq [6450, [6451 or equiv]]
or #; background in molecular biology recommended)
|
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Introduction to statistical problems arising
in molecular biology. Problems in physical mapping (radiation
hybrid mapping, DDP), genetic mapping (pedigree analysis,
lod scores, TDT), biopolymer sequence analysis (alignment,
motif recognition), and micro array analysis.
|
Effective: Fall 2005
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PUBH 7450.
Survival Analysis.
|
(3.0 cr; prereq [7406 or equiv],7407,
Stat 5102)
|
Statistical methodologies in analysis
of survival data, including Kaplan-Meier estimator, Cox's proportional
hazards multiple regression model, time-dependent covariates,
analysis of residuals, and multiple failure outcomes. Typical
biomedical applications, including clinical trials and person-years
data.
|
Effective: Fall 2005
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PUBH 7455.
Modern Nonparametrics.
|
(3.0 cr; prereq 7406, Stat 5102, MPH or
grad student or #)
| Classical nonparametric inference, exact tests and confidence intervals, robust estimates, the jackknife, bootstrap and cross-validation, nonparametric smoothing and classification trees. Variety of models and applications; formal development sufficient for understanding statistical structures and properties. Substantial computing.
|
Effective: Fall 2005
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PUBH 7460. Advanced Statistical Computing.
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(3.0 cr; prereq [7405, biostatistics
major, [C or FORTRAN]] or #)
|
Statistical computing using
SAS, Splus, and FORTRAN or C. Use of pseudo-random
number generators, distribution functions. Matrix
manipulations with applications to regression and
estimation of variance. Simulation studies, minimization
of functions, nonlinear regression, macro programming,
numerical methods of integration.
|
Effective: Fall 2005
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PUBH 7465. Biostatistics Consulting Seminar.
|
(2.0 cr; prereq [7406, biostatistics
major] or #; S-N only)
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Professional roles/responsibilities
of practicing biostatistician as consultant/collaborator
in health science research. Discussion, written
assignments, student presentations, meeting notes,
interviews, guests.
|
Effective: Fall 2005
|
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PUBH
7494. Master's Project: Biostatistics.
|
(1.0-3.0 cr; prereq [Bio MPH or
grad student], # ; S-N only)
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Directed research toward completion
of Master's or Plan B project in biostatistics.
|
Effective: Fall 2005
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PUBH 8400. Topics: Biostatistics.
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(1.0-4.0 cr; prereq # )
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New course offerings or topics of
interest in biostatistics.
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Effective: Fall 2005
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PUBH 8432.
Probability Models for Biostatistics.
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(3.0 cr; prereq 7450, 7407, Stat 5102,
advanced biostats or stats major or #)
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Three basic models used for stochastic
processes in the biomedical sciences: point processes (with
emphasis on Poisson processes), Markov processes (with emphasis
on Markov chains), and Brownian motion. Probability structure
and statistical inference studied for each process.
|
Effective: Fall 2005
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PUBH 8442.
Bayesian Decision Theory and Data Analysis.
|
(3.0 cr; prereq [[7460 or experience with
FORTRAN or with [C, S+]], Stat 5101, Stat 5102, Stat 8311, grad
student in [biostatistics or statistics] or #)
| Theory/application of Bayesian methods. Bayesian methods compared with traditional, frequentist methods.
|
Effective: Fall 2005
|
PUBH
8444. FTE: Doctoral.
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(1.0 cr; prereq Doctoral student,
adviser and DGS consent)
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(No description)
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Effective: Fall 1999
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PUBH 8452.
Advanced Longitudinal Data Analysis.
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(3.0 cr; prereq [Stat 5101, Stat 8311,
experience with [SAS or S+], advanced [biostat or stat] student]
or #)
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Methods of inference for outcome variables
measured repeatedly in time or space. Linear/nonlinear models
with either normal or non-normal error structures. Random effects.
Transitional/marginal models with biomedical applications.
|
Effective: Fall 2005
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PUBH 8462.
Advanced Survival Analysis.
|
(3.0 cr; prereq [[7450, 8432, Stat 5102],
Stat 8112 preferred, advanced [biostatistics or statistics]
major] or #)
|
Statistical methods for counting processes.
Martingale theory (transforms, predictable processes, Doob decomposition,
convergence, submartingales). Applications to nonparametric
intensity estimation. Additive and relative risk models. Inference
for event history data, recurrent events, multivariate survival,
and diagnostics.
|
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Effective: Fall
2005
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PUBH 8472.
Spatial Biostatistics.
|
(3.0 cr; prereq Stat 5101, Stat 5102,
some experience with S-plus; [8442], Stat 8311 are recommended)
| Spatial data, spatial statistical models, and spatial inference on unknown parameters or unobserved spatial data. Introduces the nature of spatial data and the special analysis tools that help to analyse such data. Follows a blend of theory and applications.
|
Effective: Fall 2005
|
PUBH
8482. Sequential Analysis.
|
(3.0 cr; prereq 7450, 8432, Stat
5102, Stat 8112 preferred, advanced biostats or stats
major or #)
|
Statistical methods for design and
analysis of sequential experiments. Wald theorems, stopping
times, martingales, Brownian motion, dymamic programming.
Compares Bayesian/fequentist approaches. Emphasizes applications
to interim monitoring of clinical trials, medical surveillance.
|
Effective: Fall 2005
|
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PUBH 8494.
Directed Research: Biostatistics.
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(1.0-4.0 cr; prereq #; S-N only)
|
Research, with direction from a faculty
member, in biostatistics.
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Effective: Fall 2002
|
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