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How should I analyze data that is paired and also repeatedly measured?

The answer will differ depend on whether or not the subjects are receiving training on the same topic each day. For instance, if the questions is about training retention and the topics differ each ...
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How should I analyze data that is paired and also repeatedly measured?

I don't have a named test for you, but here is how I would try modelling this data. Let $X^{(i,t)}=1\dots 10$ be the results of $i$-th individual observed either before ($t=0$) or after ($t=1$) ...
• 576

Is a correction for sphericity violation needed for post-hoc comparisons following repeated-measures ANOVA?

After some more reading around, this issue is addressed in a document by Paulo Gentil The Greenhouse–Geisser correction for a sphericity violation modifies the degrees of freedom in the ANOVA. That ...
1 vote
Accepted

How do I calculate the power and effect size for the Wald-type statistic of the RM-function from the MANOVA.RM package in R?

First, as this page and its many links explain, the time to do power calculations is before you do the study. A power estimate is just your chance of finding a "significant" result if the ...
• 92.5k

Within subject experiments done by (some) Psychologists

Talking about the definition of the term "experiment", I think it is fulfilled if they first have a research hypothesis, and then what they run is planned in such a way that they can control ...
• 23.8k
1 vote

Additional covariate reduces AIC in mixed models (LMM, GLMM, GAM)

If you are going to use AIC as your sole criterion for model selection, then yes. But I wouldn't recommend that, for most cases. You don't say what your dependent variable was or what sort of study ...
• 120k
Accepted

• 30.4k
Accepted

Relating the correlation coefficient to average absolute differences between two repeated and correlated measurements on the same subjects?

For two correlated variables, $X$ and $Y$, the difference is a normal distributed variable with variance and mean  \begin{array}{rcl} \mu' &=& \mu_X-\mu_Y \\ \sigma' &=& \sqrt{ \...
• 78.5k

exclude random effects component for a repeated measure

Although the (ICC) based on SubjectID suggests moderate correlation (0.5-0.7), I've opted not to include SubjectID as a random component in the model due to lack of interest in predicting individual ...
• 23.8k
Accepted

exclude random effects component for a repeated measure

If you want to capture the subject correlation in a multilevel model, I think you have to include it as a random effect, and this doesn't really depend on wanting to predict individual scores over ...
• 120k
Accepted

Assessing bivariate change (pre- and post-intervention) when sample size is small and there is no control group?

This is the within-participant mediation approach describes in Montoya, A. K., & Hayes, A. F. (2017). Two-condition within-participant statistical mediation analysis : a path-analytic framework. ...
• 668
Accepted

total variability/pattern analysis of multivariate longitudinal data for each subject

The first problem is having only 3 individuals, with only 1 dying. It's essentially impossible to get reliable results in this situation. A pattern that is equally likely between those who will die ...
• 92.5k
1 vote

mixed effect model in R with unstructured covariance

Although the question is formulated as a programming/syntax problem I will answer it, because I'm not sure if you are aware of the many other options to model (co)variance matrices over "weeks&...
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