You will learn methods for analyzing and understanding data with binary outcomes and with count outcomes. You will learn how to analyze data from hierarchical studies. You will learn the basic elements of analyzing survival data.
Specific goals of the class are:
To use logistic regression to study binary data.
To analyze binary data from experiments and from case-control designs.
To adjust for possible confounding variables.
To use the Mantel-Haenszel test.
The importance of odds ratios for summarizing studies with binary data.
The meaning of likelihood and its use in estimating
statistical models and testing hypotheses.
To learn the Poisson distribution and its use in modeling count data.
To learn methods for analyzing count data.
Statistical inference for standardized mortality and morbidity
ratios (SMR's).
To use Poisson regression to model count data.
To recognize hierarchical data structure and how it relates
to the assumption of statistically independent data .
To carry out and interpret a repeated measures analysis of
variance.
To use the linear mixed model for general hierarchical
data and for longitudinal studies.
To analyze survival data, with methods to account for censored
observations .
To construct and interpret Kaplan-Meier plots.
To carry out the log rank test, and other related tests,
for comparing survival curves.
To fit and interpret the Cox proportional hazards regression
model, which enables inclusion of additional covariates in a
survival analysis.