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Repeated Measures

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

by Karen Grace-Martin  2 Comments

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 repeated measures design is one where each subject is measured repeatedly over time, space, or condition on the dependent variable. 

These repeated measurements on the same subject are not independent of each other. They’re clustered. They are more correlated to each other than they are to responses from other subjects. Even if both subjects are in the same condition.  [Read more…] about Three Designs that Look Like Repeated Measures, But Aren’t

Tagged With: autocorrelation, clustered data, communicate results, correlated variable, Repeated Measures

Related Posts

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  • The Difference Between Clustered, Longitudinal, and Repeated Measures Data
  • Can I Treat 5 Waves of Repeated Measurements as Categorical or Continuous?
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Member Training: Elements of Experimental Design

by Karen Grace-Martin 

Whether or not you run experiments, there are elements of experimental design that affect how you need to analyze many types of studies.

The most fundamental of these are replication, randomization, and blocking. These key design elements come up in studies under all sorts of names: trials, replicates, multi-level nesting, repeated measures. Any data set that requires mixed or multilevel models has some of these design elements. [Read more…] about Member Training: Elements of Experimental Design

Tagged With: ANOVA, blocking, Crossed factors, Crossover Design, Latin squares, multilevel model, nested models, Regression, Repeated Measures, replication

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What is the Purpose of a Generalized Linear Mixed Model?

by Kim Love  1 Comment

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 purpose of a GLMM.

Mixed effects models are useful when we have data with more than one source of random variability. For example, an outcome may be measured more than once on the same person (repeated measures taken over time).

When we do that we have to account for both within-person and across-person variability. A single measure of residual variance can’t account for both.

[Read more…] about What is the Purpose of a Generalized Linear Mixed Model?

Tagged With: generalized linear mixed model, random effect, Repeated Measures

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What Is Regression to the Mean?

by Audrey Schnell  Leave a Comment

by Audrey Schnell, PhDStage 2

Have you ever heard that “2 tall parents will have shorter children”?

This phenomenon, known as regression to the mean, has been used to explain everything from patterns in hereditary stature (as Galton first did in 1886) to why movie sequels or sophomore albums so often flop.

So just what is regression to the mean (RTM)? [Read more…] about What Is Regression to the Mean?

Tagged With: pre-post design, regression to the mean, Repeated Measures, two-phase sampling

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Can I Treat 5 Waves of Repeated Measurements as Categorical or Continuous?

by Karen Grace-Martin  2 Comments

Question: Can you talk more about categorical and repeated Time? If I have 5 waves at ages 0, 1  year, 3 years, 5 years, and 9 years, would that be categorical or repeated? Does mixed account for different spacing in time?

 

Mixed models can account for different spacing in time and you’re right, it entirely depends on whether you treat Time as categorical or continuous.

First let me mention that not all designs can treat time as either categorical or continuous. The reason it could go either way in your example is because time is measured discretely, yet there are enough numerical values that you could fit a line to it. [Read more…] about Can I Treat 5 Waves of Repeated Measurements as Categorical or Continuous?

Tagged With: continuous time, linear mixed model, Repeated Measures

Related Posts

  • Six Differences Between Repeated Measures ANOVA and Linear Mixed Models
  • Linear Mixed Models for Missing Data in Pre-Post Studies
  • Mixed Models: Can you specify a predictor as both fixed and random?
  • Three Designs that Look Like Repeated Measures, But Aren’t

Six Differences Between Repeated Measures ANOVA and Linear Mixed Models

by Karen Grace-Martin  13 Comments

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 the much simpler and easier-to-understand repeated measures ANOVA.

One thing that makes the decision harder is sometimes the results are exactly the same from the two models and sometimes the results are [Read more…] about Six Differences Between Repeated Measures ANOVA and Linear Mixed Models

Tagged With: ANOVA, clustered data, linear mixed model, Missing Data, mixed model, Repeated Measures, repeated measures anova, unbalanced data

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  • Linear Mixed Models for Missing Data in Pre-Post Studies
  • Five Advantages of Running Repeated Measures ANOVA as a Mixed Model
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  • Approaches to Repeated Measures Data: Repeated Measures ANOVA, Marginal, and Mixed Models

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