Linked Questions

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 ...
66
votes
18answers
88k views

Statistics interview questions

I am looking for some statistics (and probability, I guess) interview questions, from the most basic through the more advanced. Answers are not necessary (although links to specific questions on this ...
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: ...
28
votes
1answer
23k views

What is the difference between generalized estimating equations and GLMM?

I'm running a GEE on 3-level unbalanced data, using a logit link. How does this differ (in terms of the conclusions I can draw and the meaning of the coefficients) from a GLM with mixed effects (GLMM)...
9
votes
1answer
17k 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
13k views

What test is appropriate for binary outcome with repeated measures and binary, ordinal and continuous independent variables?

I'm trying to figure out what is the most appropriate statistic test for use with my data and was hoping for some advice. The primary data consists of a binary independent variable (patient test - ...
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. ...
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 ...
2
votes
1answer
7k views

Getting the variance-covariance matrix of regression coefficients in GEE

I fitted a GEE model using the function genZcor with user defined correlation matrix. I want to get the var-cov matrix of the regression coefficients. But 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\...
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 ...
5
votes
1answer
2k views

Interpreting coefficients of ordinal logistic regression when there is clustering within the data

I have built and refined a regression model using the ordinal package in R. The measure is $0>1>2>3>4>5$ (Yes/No ...
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 ...
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 ...
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 ...

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