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OptinMon 21 - Random Intercept and Random Slope Models

Confusing Statistical Term #10: Mixed and Multilevel Models

by Karen Grace-Martin  5 Comments

What’s the difference between Mixed and Multilevel Models? What about Hierarchical Models or Random Effects models?

I get this question a lot.

The answer: very little.

[Read more…] about Confusing Statistical Term #10: Mixed and Multilevel Models

Tagged With: crossed random effects, hierarchical linear model, individual growth curve model, mixed effects model, mixed model, multilevel model, random coefficient model, random effect, random intercept, Random Slope Model

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  • Is there a fix if the data is not normally distributed?
  • What packages allow you to deal with random intercept and random slope models in R?

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

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  • Can I Treat 5 Waves of Repeated Measurements as Categorical or Continuous?
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Multilevel, Hierarchical, and Mixed Models–Questions about Terminology

by Karen Grace-Martin  Leave a Comment

Multilevel models and Mixed Models are generally the same thing. In our recent webinar on the basics of mixed models, Random Intercept and Random Slope Models, we had a number of questions about terminology that I’m going to answer here.

If you want to see the full recording of the webinar, get it here. It’s free.

Q: Is this different from multi-level modeling?

A: No. I don’t really know the history of why we have the different names, but the difference in multilevel modeling [Read more…] about Multilevel, Hierarchical, and Mixed Models–Questions about Terminology

Tagged With: fixed effect, Fixed Factor, hierarchical linear model, mixed model, multilevel model, panel data, random effect, Random Factor

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Is there a fix if the data is not normally distributed?

by Karen Grace-Martin  Leave a Comment

In this video I will answer another question from a recent webinar, Random Intercept and Random Slope Models.

We are answering questions here because we had over 500 people live on the webinar so we didn’t have time to get through all the questions.

[Read more…] about Is there a fix if the data is not normally distributed?

Tagged With: covariance terms, linear mixed model, random effect, random intercept, random slope

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  • What is the intercept for each individual in a random slope model?
  • Impact of Covariance Terms on Random Slope Model
  • How to Use the Fitted Mixed Model to Calculate Predicted Values

What packages allow you to deal with random intercept and random slope models in R?

by Karen Grace-Martin  1 Comment

In this video I will answer a question from a recent webinar, Random Intercept and Random Slope Models.

We are answering questions here because we had over 500 people live on the webinar so we didn’t have time to get through all the questions.

[Read more…] about What packages allow you to deal with random intercept and random slope models in R?

Tagged With: covariance terms, linear mixed model, random effect, random intercept, random slope

Related Posts

  • Is there a fix if the data is not normally distributed?
  • What is the intercept for each individual in a random slope model?
  • Impact of Covariance Terms on Random Slope Model
  • How to Use the Fitted Mixed Model to Calculate Predicted Values

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

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