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Results tagged with mixed-model
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user 222364
Mixed (aka multilevel or hierarchical) models are linear models that include both fixed effects and random effects. They are used to model longitudinal or nested data.
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How to combine random effect and nested random effect with lme
I'm not sure how to do it in package NLME, but with LME4 you could do it with:
lmer(y ~ t + x + (1 + T|SUBJECT:SCHOOL), REML = FALSE)
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Its my model a Mixed model?
Compute the Intraclass Correlation Coefficient of your data by specifying person, or model, if it is non-zero, you likely have a mixed model. This can be done by "hand" or with many different packages …
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4
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1
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Centering in longitudinal linear mixed modeling - center by participant mean, timepoint mean...
EDIT: I was incorrectly looking to center my outcome variables. Only center predictors, and decide on group mean or grand mean centering by how you want to interpret your intercept.
I have 150 partic …
- 153
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Dealing with heteroscedasticity and non-normality in a mixed model
You could attempt to do a robust linear mixed model using package robustlmm.
https://cran.r-project.org/web/packages/robustlmm/index.html
Or you can try it in lme4 with glmer() based on the appropri …
- 153
4
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Accounting for grouped random effects in lme4
If you believe the different categories vary in terms of their measurement and you want to test that, you need to model the category as a random intercept with (1|category).
However, I think we need …
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3
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1
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Doing a multilevel model using lmer with participants nested in time - should time be a fact...
I am using function lmer() within package "lme4". Repeated-measures design with 4 time points, data is in long format. The time points are equidistant apart. Should I treat that variable as an integer …
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