Linked Questions

1
vote
0answers
62 views

GEE vs GLMM in this example [duplicate]

I am fitting a model with a dichotomous outcome, large number of subjects measured at differing visit (visit 1-14) with four other categorical and cont outcome variable....the main question is if the ...
65
votes
3answers
69k views

When to use generalized estimating equations vs. mixed effects models?

I have been quite happily using mixed effects models for a while now with longitudinal data. I wish I could fit AR relationships in lmer (I think I'm right that I can't do this?) but I don't think it'...
35
votes
3answers
46k views

Difference between generalized linear models & generalized linear mixed models

I am wondering what the differences are between mixed and unmixed GLMs. For instance, in SPSS the drop down menu allows users to fit either: ...
9
votes
1answer
16k views

What is the difference between GLM and GEE?

Whats the difference between a GLM model (logistic regression) with a binary response variable which includes subject and time as covariates and the analogous GEE model which takes into account ...
5
votes
1answer
7k views

GLM with Temporal Data

This is my first post on here, looking for some help. I am relatively new to analysis of temporal datasets. I have experience with R and developing linear models, so I am trying to figure out if the ...
6
votes
3answers
1k views

Which logit or probit model should I use for multiple response / dependent variables?

I have $300$ time series objects that constitute the $300$ columns of matrix $X$. This matrix has $5$ rows and represents $5$ days of time series information for each $300$ columns. I set up a $300\...
3
votes
1answer
2k views

In what sense is the interpretation of coefficients in a GLMM subject-specific?

There is something I'm not quite understanding conceptually about the output from generalized linear mixed models. I have read that the target of inference in GLMMs is subject-specific. For example, ...
1
vote
0answers
976 views

Advantages and Disadvantages of GLMM and GEE

I am making a list of disadvantages of GEE and GLMM for a correlated binary outcome. So far I know that GEE requires a relatively large number of clusters, and that it produces profile curves that ...
0
votes
1answer
547 views

Regression model for country-year level data

I have a data set which includes country-years and I am interested in modeling founding and mortality for corporations in each country-year. I am interested in within- as well as between-country ...
0
votes
0answers
114 views

Comparison between multi-level modelling and generalized estimating equation [duplicate]

Possible Duplicate: When to use generalized estimating equations vs. mixed effects models? I have a dataset from collected by cluster randomized sampling, I did a logistic regression on this ...
0
votes
2answers
100 views

GLMM model error

I have data on security incidents of various companies. I am trying to predict the 'time to discovery' using covariates such as 'motive of security incident', 'pattern of security incident', 'company ...