Tagged Questions
1
vote
0answers
35 views
How do I set up a multivariate hierarchical multiple linear regression in R?
I have two continuous DVs (measurements taken on individual fish), one continuous individual level IV (fish's size), and two site-level IVs (PC1 and PC4). Sites are either take or no take. There are ...
3
votes
0answers
48 views
Nesting, sort-of: Multiple observations mapping to a single DV measure?
This is a made up example, but it gets to a point I am trying to figure out.
I know that you can use a nested model if your IVs are collected in clusters -- for example, if you want to model the ...
1
vote
1answer
356 views
Methods to find the relationships between independent and dependent variables instead of regression
Which statistical method can be used to find the relationships between independent and dependent variables instead of regression? And their advantages over regression.
It should be mentioned I am not ...
1
vote
1answer
390 views
Categorical fixed effect w/ 3 levels in LMER
I have a categorical fixed effect with 3 levels that I'm trying to enter into an LME.
...
4
votes
1answer
343 views
Fitting a particular Gaussian model
Using R or SAS, I want to fit the following Gaussian model:
$$
\begin{pmatrix}
y_{1j1} \\ y_{1j2} \\ y_{1j3} \\ y_{2j1} \\ y_{2j2} \\ y_{2j3}
\end{pmatrix}
\sim_{\text{i.i.d.}}
{\cal N}
...
2
votes
1answer
1k views
How to interpret two-way interactions in Linear Mixed Effects modeling?
I've fit a Linear Mixed Effects model to some "accuracy" scores for a study with rats. The fixed effects are TrialNumber and ...
3
votes
0answers
434 views
R: How to “control” for another variable in Linear Mixed Effects Regression model?
Essentially, I have two collinear variables which could be seen as either random or as fixed effects, a dependent variable I'm fitting the model to, and a variable that's assuredly a random effect.
...
