Search Results (search words: repeated measures)

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The Wide and Long Data Format for Repeated Measures Data

One issue in data analysis that feels like it should be obvious, but often isn't, is setting up your data. The kinds of issues involved ... Continue Reading

The Difference Between Clustered, Longitudinal, and Repeated Measures Data

What is the difference between Clustered, Longitudinal, and Repeated Measures Data?  You can use mixed models to analyze all of them. But the issues ... Continue Reading

An Example of Specifying Within-Subjects Factors in Repeated Measures

Some repeated measures designs make it quite challenging to  specify within-subjects factors. Especially difficult is when the design contains two ... Continue Reading

Three Designs that Look Like Repeated Measures, But Aren’t

Repeated measures is one of those terms in statistics that sounds like it could apply to many design situations. In fact, it describes only one. A ... Continue Reading

Six Differences Between Repeated Measures ANOVA and Linear Mixed Models

As mixed models are becoming more widespread, there is a lot of confusion about when to use these more flexible but complicated models and when to use ... Continue Reading

Models for Repeated Measures Continuous, Categorical, and Count Data

Lately, I've gotten a lot of questions about learning how to run models for repeated measures data that isn't continuous. Mostly categorical. But ... Continue Reading

Why Mixed Models are Harder in Repeated Measures Designs: G-Side and R-Side Modeling

I have recently worked with two clients who were running generalized linear mixed models in SPSS. Both had repeated measures experiments with a ... Continue Reading

When Does Repeated Measures ANOVA not work for Repeated Measures Data?

Repeated measures ANOVA is the approach most of us learned in stats classes for repeated measures and longitudinal data. It works very well in certain ... Continue Reading

Analyzing Pre-Post Data with Repeated Measures or ANCOVA

One area in statistics where I see conflicting advice is how to analyze pre-post data. I've seen this myself in consulting. A few years ago, I ... Continue Reading

The Repeated and Random Statements in Mixed Models for Repeated Measures

"Because mixed models are more complex and more flexible than the general linear model, the potential for confusion and errors is higher." - Hamer ... Continue Reading

Approaches to Repeated Measures Data: Repeated Measures ANOVA, Marginal, and Mixed Models

There are three main ways you can approach analyzing repeated measures data, assuming the dependent variable is measured continuously: repeated ... Continue Reading

Five Advantages of Running Repeated Measures ANOVA as a Mixed Model

There are two ways to run a repeated measures analysis.The traditional way is to treat it as a multivariate test--each response is considered a ... Continue Reading

What is the Purpose of a Generalized Linear Mixed Model?

If you are new to using generalized linear mixed effects models, or if you have heard of them but never used them, you might be wondering about the ... Continue Reading

Linear Mixed Models for Missing Data in Pre-Post Studies

In the past few months, I've gotten the same question from a few clients about using linear mixed models for repeated measures data.  They want to ... Continue Reading

The Difference Between a Chi-Square Test and a McNemar Test

You may have heard of McNemar tests as a repeated measures version of a chi-square test of independence. This is basically true, and I wanted to show ... Continue Reading

Three Issues in Sample Size Estimates for Multilevel Models

If you've ever worked with multilevel models, you know that they are an extension of linear models. For a researcher learning them, this is both good ... Continue Reading

Sample Size Estimates for Multilevel Randomized Trials

If you learned much about calculating power or sample sizes in your statistics classes, chances are, it was on something very, very simple, like a ... Continue Reading

The Difference Between Crossed and Nested Factors

One of those tricky, but necessary, concepts in statistics is the difference between crossed and nested factors. As a reminder, a factor is any ... Continue Reading

Member Training: Interactions in Poisson and Logistic Regression – Part 2

Interactions in statistical models are never especially easy to interpret. Throw in non-normal outcome variables and non-linear prediction functions ... Continue Reading

Concepts in Linear Regression to know before learning Multilevel Models

Are you learning Multilevel Models? Do you feel ready? Or in over your head? It's a very common analysis to need to use. I have to say, learning it ... Continue Reading

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Statistical Consulting Services

statistical consulting Sometimes you need one-on-one intensive guidance. With ... Continue Reading

Statistical Consulting Services: Hourly

Hourly Statistical Consulting For when you need guidance and advice for a statistical plan or analysis. Perfect if you have: a need for help to ... Continue Reading


Currently Enrolling Interpreting (Even Tricky) Regression Coefficients Instructor: Karen Grace-Martin Stage: 2, Linear ... Continue Reading

Data Analysis Practice and Skills

Resources to improve your data analysis practice and skills As a data analyst, it's not enough to understand statistics or to be able to use the ... Continue Reading


learn R The statistical programming language R is becoming a popular means for analyzing data. But it’s not always easy to use. We have a number of ... Continue Reading

Logistic Regression

logistic regression resources Listed below are workshops, trainings, and articles to help you learn logistic regression. Logistic regression is an ... Continue Reading

Mixed and Multilevel Models

mixed and multilevel models resources Listed below are workshops, trainings, and articles to help you learn Mixed, Hierarchical, and Multilevel ... Continue Reading

Analysis of Variance and Covariance

analysis of variance and covariance resources Listed below are workshops, trainings, and articles to help you learn Analysis of Variance (ANOVA) and ... Continue Reading

Missing Data

missing data resources I don't need to tell you, missing data stinks. And frankly, it's in just about every data set. These days, though, there are ... Continue Reading