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GLM for Count Data

Generalized Linear Models

Generalized linear models for count data are regression techniques available for modeling outcome...

Updated 2 years ago by Elkip

Mutlivariate and Joint Models for Longitudinal Data

Analysis of Correlated Data

Longitudinal studies are commonly designed in many research fields in order to see changes over a...

Updated 2 years ago by Elkip

Interim Analysis and Data Monitoring

Applied Statistics in Clinical Trials

Clinical trials are often longitudinal in nature. It is often impossible to enroll all subjects a...

Updated 2 years ago by Elkip

Multiple Imputation

Analysis of Correlated Data

If no missing data is present our statistical methods provide valid inference only if the followi...

Updated 2 years ago by Elkip

Effect Modification and Interaction

Applied Statistics in Clinical Trials

Interaction is when a treatment effect is different across different subgroups of the population ...

Updated 2 years ago by Elkip

GLM for Multinomial Outcomes

Generalized Linear Models

Multinomial outcomes are much akin to binomial outcomes, with added complexity due to outcomes wi...

Updated 2 years ago by Elkip

Multi-Level Modeling

Analysis of Correlated Data

Recall the core of mixed models is that they incorporate fixed and random effects. While single  ...

Updated 2 years ago by Elkip

Non-Inferiority in Clinical Trials

Applied Statistics in Clinical Trials

Usually clinical trials should show if a new treatment is superior to placebo or no treatment, bu...

Updated 2 years ago by Elkip

Generalized Linear Mixed Effects Models

Analysis of Correlated Data

Generalized Linear Mixed Models (GLMMs) are an extension of linear mixed models to allow response...

Updated 2 years ago by Elkip

Introduction to Bayesian Modeling

Bayesian Modeling in Biomedical Research

In the frequentist approach, estimated probabilities are viewed as one of an infinite sequence of...

Updated 2 years ago by Elkip

Hypothesis Testing with GLM

Generalized Linear Models

Effect modification can be modeled with logistic regression by including interaction terms. A sig...

Updated 2 years ago by Elkip

Hierarchical Models

Bayesian Modeling in Biomedical Research

Previously we have assumed given covariates, the observations are independent. However, there are...

Updated 2 years ago by Elkip

Multiple Comparisons

Applied Statistics in Clinical Trials

There are some situations where it may be necessary to have multiple hypothesis tests; ANOVA with...

Updated 2 years ago by Elkip

Marginal Methods

Analysis of Correlated Data

In many biomedical applications outcomes are binary, ordinal or a count. In such cases we conside...

Updated 2 years ago by Elkip

Survival Analysis in Clinical Trials

Applied Statistics in Clinical Trials

We've already covered survival analysis in great detail here. This will be review, application to...

Updated 2 years ago by Elkip

Linear Mixed Effects Models II

Analysis of Correlated Data

The simplest mixed effect model is a random intercept model where Zi = 1; The random intercept mo...

Updated 2 years ago by Elkip

Linear Mixed Effects Models I

Analysis of Correlated Data

Here we'll be considering an alternative approach for analyzing longitudinal data using linear mi...

Updated 2 years ago by Elkip

Binomial Outcomes

Generalized Linear Models

Frequently dichotomous outcomes are used in medical studies, such as presence of a disease or exp...

Updated 2 years ago by Elkip

Bayesian Logistic Regression

Bayesian Modeling in Biomedical Research

Let Y be an indicator for presence of disease ->    Y | p ~ Bin(p, 1) Logistic regression models...

Updated 2 years ago by Elkip

Baseline Variable Adjustment

Applied Statistics in Clinical Trials

Baseline covariates are variables expected to influence the outcome, measured before the start of...

Updated 2 years ago by Elkip