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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.
3
votes
1
answer
70
views
Is random slope meaningful when the relevant fixed effect is not significant?
I am building a liner mixed model with the following syntax:
$$
y \sim \text{run} + (1 + \text{run} \mid \text{subjects})
$$
The summary is as follows:
The fixed effect of $\text{run}$ is not signifi …
3
votes
1
answer
38
views
If measured in different time across days, should it be crossed or nested random effects?
everyone.
I have a dataset that happiness was measured in morning, afternoon and evening(time of day) across 3-6 days for each subject.
My two questions are:
If I care about the relationship between …
0
votes
0
answers
67
views
How to do moderated mediation analysis with linear mixed model with nested random effect?
I want to build a model like this. All variables are continuous variables. Each subject was measured for many times across days, so this should be done with a linear mixed model I guess. What's more, …
1
vote
1
answer
112
views
Should I contain time as a random variable in repeated measurement?
I have a dataset which contains happiness scores of several subjects, measured three times within a day (in morning, afternoon and evening) and repeated across several days. But during how many days h …
4
votes
0
answers
206
views
In linear mixed model, what if the dependent variable is repetitive for a random factor?
(1) Research background:
My research design involves having each participant complete multiple trials to assess their happiness rating while simultaneously recording EEG data. Each participant has dif …