Linked Questions

1
vote
1answer
55 views

How to isolate the effect of dichotomous predictor?

I want to isolate gender differences in preferences for a particular attribute of a product based on data available about their product purchases. I understand that I have to use a mixed Poisson ...
1
vote
0answers
385 views

GEE and GLS. Are they similar?

First of all there is another question about it here, but it has no answers unfortunately...And also here, but it is more general about mixed models and GEE, while my question is more specific... So, ...
2
votes
0answers
128 views

Confidence intervals and hypothesis tests for binary choice data with repeated measures

I have data with two between-subjects factors (each with two levels; bs1 has levels ‘hi’ and ‘lo’, and bs2 has levels ‘happy’ and ‘sad’) and one within-subjects factor (ws1, with levels ‘good’, ‘...
2
votes
1answer
105 views

Which ANOVA test to use in this experimental design?

I have an experimental design as follows: Three groups of cakes: treatment A, treatment B, control; Three replicates per cake. They are observed during 10 days for microbial growth. My interest is ...
1
vote
1answer
347 views

GEE with longitudinal, mixed-effect data

I have a data set with a binomial response and am trying to determine the best way to model it. Based off of this post I believe I need to use a GEE vs a mixed effect model since I am interested in ...
1
vote
1answer
1k 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 ...
3
votes
1answer
3k views

Interpret effect of adding random effects to ordinal regression (R - ordinal package - clmm)

I know there are already lots of questions around this topic (especially this one and this one) but I haven't really seen anything that directly helps me (It will be obvious I'm not a great ...
1
vote
2answers
10k views

Interpretation of GEE coefficients

Suppose blood pressure is a continuous outcome variable and you run a linear GEE with following predictors: age (years), weight (lbs), and smoking (yes/no). How would you interpret the coefficients ...
6
votes
1answer
2k views

Logistic Regression with dependent observations

I have a dataset that contains 100 different patients over 5 year’s period. Every patient is examined each month with regard to particular illness and marked as healthy or ill (0 or 1). Every person ...
2
votes
2answers
2k views

Regression with repeated measures in Matlab

Is there a way to perform multiple logistic regression on repeated measures data using Matlab? I have a data set containing a daily measurement recorded from 20 participants for 60 days. I am ...
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\...
0
votes
0answers
116 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 ...
7
votes
1answer
6k views

GEE with exchangeable working covariance vs. assuming independence and using Huber-White standard errors?

I'm analyzing a dataset including 13000 students. Students are clustered into schools/grades. The ICC (intraclass correlation coefficient) shows that students in a same school are correlated. ...
35
votes
3answers
49k 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: ...
6
votes
1answer
3k views

How does a generalized linear mixed model estimate means and how does this differ from calculating means by hand?

I've recently read a paper which used generalised linear mixed models to estimate mean annual and monthly values for the response variable in the model. The response variable was a normally ...

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