3
votes
Accepted
Linear mixed effects modeling with MZ and DZ twin pairs
Comments:
To understand the statement "This step allows the method to be generalizable to other cohorts since we are treating the individuals as if they were unrelated.", consider Figure 1 ...
- 2,156
2
votes
Random Effect in twin study of both MZ and DZ twin pairs
I answer your question about the linear mixed model(s) for microbiome gene/species abundances by New et al. described in [1]. You already asked a very similar question here.
In the New et al. paper, ...
- 2,156
2
votes
Accepted
How to deal with crossed and nested factors at the same time in a linear mixed model?
If I understand correctly, Event represents the type of event identified to the investigator (personal versus news story, independent of the particular nature of ...
- 62.4k
1
vote
Multilevel model for education data, if individuals within cluster change (school) between time points
I'm fairly sure this is a classic case of multiple membership, and there are models that have been proposed to account for things like this:
https://arxiv.org/abs/1907.04148#:~:text=Multiple%...
- 425
1
vote
Accepted
question of a Poisson random effect model
Start with your first expression:
$$\log E(Y_{i}|b_i,x_i)=\beta_0+\beta_1x_i+b_i$$
The effect of a one-unit change in $x_i$ is easy to write:
$$\log E(Y|x_i+1,b_i) - \log E(Y|x_i,b_i) = \beta_0+\...
- 32.7k
1
vote
Accepted
Can causal relationships be inferred from a random effects panel model?
I would say, yes, causal relationships can be inferred from random effects panel models under certain circumstances, especially random assignment of a treatment. Unfortunately, I would say no, you ...
- 130
1
vote
Why is there heteroskedasticity even though no relationship seems present in the residual plot?
First, focus onthe first plot, without outlier removal: To me it is clear that the spread of the points around the horizontal zero line is increasing with increasing fitted values! If you calculate ...
- 64.9k
1
vote
How is the standard deviation of random effects estimated?
Suppose that your model is something like
$$
y_{ij} = \beta + u_j + \varepsilon_{ij}
$$
where $u_j \sim \mathcal{N}(0, \sigma^2_u)$, for $j=1,\ldots,m$, are the random intercepts and $\varepsilon_{ij} ...
- 131
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