# Applied Biostatistics in Clinical Research

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```					Applied Biostatistics in Clinical
Research
Required test

• Regression Methods in Biostatistics
Linear, Logistic, Survival, and Repeated
Measured Models

• By Eric Vittinghoff, David V. Glidden,
Stephen C. Chiboski, Charles E.
McCulloch
Longitudinal methods

• All of the text’s regression methods work
with longitudinal data
(the causative exposures precede the
outcomes)
Major course topics
• Linear regression
Predictive modeling of continuous outcomes

• Examples: height, blood pressure

• Explanatory variables
Binary, nominal, ordinal, continuous
Major course topics
• Logistic regression
Predictive modeling of binary outcomes

• Examples: death, developing lung cancer

• Explanatory variables
Binary, nominal, ordinal, continuous
Major course topics
• Survival analysis
Predictive modeling of time to event data

• Examples: time to death, time to
developing lung cancer

• Explanatory variables
Binary, nominal, ordinal, continuous
• Poisson Regression
• Predictive modeling of count data

• Examples: Number of emergency room
visits

• Explanatory variables
Binary, nominal, ordinal, continuous

• Clinical diagnosis with likelihood ratios
Omitted text topic
• Regression with repeated measures

• Regression using repeated measures is
the primary topic of the optional third
statistics course
Examples of repeated measures

• Monthly blood pressure measurements

• Single measurements of members of a
family (repeated measures of the family)
Types of repeated measures
analyses
• Patterns of change over time (change
trajectories)

• Binary, ordinal, or continuous outcomes
allowed

• Example: Physiological measures by days
post-intervention
Types of repeated measures
analyses
• Multi-level analyses

• Binary, ordinal, or continuous outcomes
allowed

• Predictors from multiple levels
• Example: Patient, physician, and hospital
characteristics
Types of repeated measures
analyses
• Multi-process analyses

• Multiple outcomes allowed
(Binary, ordinal, continuous, or time to event)

• Predictors from single or multiple levels
• Examples:
Changes in height, weight, and blood pressure
during growth
Birth in a hospital and infant survival
Optional text

• The Little SAS Book for Enterprise Guide
3.0

• By Susan Slaughter and Lora Delwich
Structure of classes
• About an hour of lecture
A clinical example, coverage of the text, and text
examples using SAS Enterprise Guide

• Student presentations of exercises related to the
lectures

• Student presentations of analyses of their class
projects

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 views: 2 posted: 2/27/2012 language: pages: 15