3 votes

How to decide whether to treat the time variable as categorical or continuous?

It is unlikely that a random effects model will adequately fit the serial correlation pattern you are likely to see in such data. See this for more. Are the four time points exactly the times at ...
Frank Harrell's user avatar
1 vote

How to decide whether to treat the time variable as categorical or continuous?

It is up to you to chose according to how the different time points relate to each other in your experiment. My intuition is that it should not change anything to the overall result. I would try both ...
CaroZ's user avatar
  • 617
1 vote

Bad model fit for a second-order growth curve with time-varying covariates. Do I have to find a way out or will it depend on the aim of the analysis?

The misfit when you add additional variables with multiple indicators can have many reasons (especially in a complex model like yours), including problems with the measurement model (e.g., correlated ...
Christian Geiser's user avatar

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