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random effect

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

Related Posts

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  • The Difference Between Random Factors and Random Effects
  • 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?

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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  • Confusing Statistical Term #10: Mixed and Multilevel Models
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The Difference Between Random Factors and Random Effects

by Karen Grace-Martin  6 Comments

Mixed models are hard.

They’re abstract, they’re a little weird, and there is not a common vocabulary or notation for them.

But they’re also extremely important to understand because many data sets require their use.

Repeated measures ANOVA has too many limitations. It just doesn’t cut it any more.

One of the most difficult parts of fitting mixed models is figuring out which random effects to include in a model. And that’s hard to do if you don’t really understand what a random effect is or how it differs from a fixed effect. [Read more…] about The Difference Between Random Factors and Random Effects

Tagged With: ANOVA, fixed variable, linear mixed model, mixed model, multilevel model, random effect, Random Factor, random intercept, random slope

Related Posts

  • Specifying Fixed and Random Factors in Mixed Models
  • Multilevel, Hierarchical, and Mixed Models–Questions about Terminology
  • 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?

Member Training: Meta-analysis

by guest contributer  Leave a Comment

Meta-analysis is the quantitative pooling of data from multiple studies. Meta-analysis done well has many strengths, including statistical power, precision in effect size estimates, and providing a summary of individual studies.

But not all meta-analyses are done well. The three threats to the validity of a meta-analytic finding are heterogeneity of study results, publication bias, and poor individual study quality.

[Read more…] about Member Training: Meta-analysis

Tagged With: effect size, fixed effect, meta-analysis, PRISMA guidelines, random effect

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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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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

Related Posts

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