7 votes
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 ...
Peter Flom's user avatar
  • 120k
6 votes

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 ...
Christian Hennig's user avatar
3 votes

LMM and RM-ANOVA differences. Which one is preferable?

I think you should use neither. I don't understand why you fit separate models instead of including the phase in the model. Your dependent variable looks like you should be using a GLMM with a ...
Roland's user avatar
  • 6,661
2 votes
Accepted

Within group vs between group variance in an RCT: how to handle?

So from what I understand: You randomized users to one of two exposures The hope is that you can detect a differences of \$ 2 dollars per user between groups However, the pre-experiment data suggests ...
Demetri Pananos's user avatar
2 votes

Measurements necessary for repeated measures model

Chapter 7 of Frank Harrell's Regression Modeling Strategies covers this situation in much more detail than is possible in an answer here. A few suggestions follow, mostly drawn from that. First, ...
EdM's user avatar
  • 92.4k
2 votes

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

Assuming bivariate normality, the mean and standard deviation of the differences are normally distributed with mean and standard deviation $\mu_d = \mu_1 - \mu_2$ and $\sigma_d = \sqrt{\sigma_1^2 + \...
COOLSerdash's user avatar
  • 30.2k
2 votes
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{ \...
Sextus Empiricus's user avatar
2 votes

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 ...
Christian Hennig's user avatar
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 ...
EdM's user avatar
  • 92.4k
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 ...
Peter Flom's user avatar
  • 120k
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&...
BenP's user avatar
  • 1,144

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