Analysis of Correlated Data
BS857: Modern methods for analyzing correlated observations in a regression framework. This course covers the design, analysis, and interpretation of correlated data studies with an emphasis on longitudinal studies. Unfortunately, my professor had no teaching ability so these notes come from publicly available resources.
Introduction to Longitudinal and Clustered Data
Correlated data occurs in a variety of situations. The four basic types: Repeated measurements...
Response Profile Analysis
Are the mean response profiles similar in the groups, or in other words, are the mean response ...
Modeling the Mean and Covariance
Suppose we have a model of mean response as a product of time on a continuous value:The top is co...
Linear Mixed Effects Models I
Here we'll be considering an alternative approach for analyzing longitudinal data using linear mi...
Linear Mixed Effects Models II
The simplest mixed effect model is a random intercept model where Zi = 1; The random intercept mo...
Marginal Methods
In many biomedical applications outcomes are binary, ordinal or a count. In such cases we conside...
Generalized Linear Mixed Effects Models
Generalized Linear Mixed Models (GLMMs) are an extension of linear mixed models to allow response...
Multi-Level Modeling
Recall the core of mixed models is that they incorporate fixed and random effects. While single ...
Multiple Imputation
If no missing data is present our statistical methods provide valid inference only if the followi...
Mutlivariate and Joint Models for Longitudinal Data
Longitudinal studies are commonly designed in many research fields in order to see changes over a...
Time Series Models
While standard regression we must assume observations are independent from one another, but with ...