Is time a random effect?
1 Answer. Time is a continuous variable, and random effects are categorical variables. Include it as a fixed effect if you think it will describe some of the variation in DS or if you think it would be valuable as part of an interaction term.
Can a continuous variable be a random effect?
First you CANNOT treat a continuous variable as a random effect. So if you are putting area or temperature or body size is in they may be a nuisance/control variable but they are a fixed effect. Of course you are only estimating one parameter (the slope) so there is no degree of freedom cost to treating it as random.
What are the advantages and disadvantages of repeated measures design?
2. Repeated Measures:
- Pro: As the same participants are used in each condition, participant variables (i.e., individual differences) are reduced.
- Con: There may be order effects.
- Pro: Fewer people are needed as they take part in all conditions (i.e. saves time).
Which is better linear mixed effect or repeated measures?
EDIT 2: I originally thought I needed to run a two-factor ANOVA with repeated measures on one factor, but I now think a linear mixed-effect model will work better for my data. I think I nearly know what needs to happen, but am still confused by few points.
When do you need a repeated statement in a mixed model?
If you need that to answer your research question, then you’ll need both the time 1 and time 2 measures as outcomes, and you need some sort of repeated measures–either a repeated measures GLM or a mixed model. You could run a random intercept (using a random statement) or a marginal model (using a repeated statement).
How to test the effect of random terms?
However, the effect of random terms can be tested by comparing the model to a model including only the fixed effects and excluding the random effects, or with the rand function from the lmerTest package if the lme4 package is used to specify the model.
How to get p-values from lmer function?
The lmer function from the lme4 package has a syntax like lm. Add something like + (1|subject) to the model for the random subject effect. To get p-values, use the car package.