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Dimitris Rizopoulos
Dimitris Rizopoulos
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What are the arguments for and against selecting GEE and Linear Mixed Models when the outcome variable is continuous? Are they any circumstances where one performs better than other?

The data I am modelling has these features:

Randomized trial, 910 subjects
15 measurement occasions (no mistimed measurements)
3 treatment groups
Continuous outcome variable but skewed at all occasions in all three groups
Question of interest: Compare mean trajectory over time among the 3 groups
Had lots of missing data with time, but assume missing is at random

Also, does the choice of using baseline measurement as covariate or as part of outcome vector matter when there are large number of repeated measurements, because the effect of baseline can usually decrease over time.

Thank you

What are the arguments for and against selecting GEE and Linear Mixed Models when the outcome variable is continuous? Are they any circumstances where one performs better than other?

The data I am modelling has these features:

Randomized trial, 910 subjects
15 measurement occasions (no mistimed measurements)
3 treatment groups
Continuous outcome variable but skewed at all occasions in all three groups
Question of interest: Compare mean trajectory over time among the 3 groups
Had lots of missing data with time, but assume missing is at random

Also, does the choice of using baseline measurement as covariate or as part of outcome vector matter when there are large number of repeated measurements, because the effect of baseline can usually decrease over time.

Thank you

What are the arguments for and against selecting GEE and Linear Mixed Models when the outcome variable is continuous? Are they any circumstances where one performs better than other?

The data I am modelling has these features:

Randomized trial, 910 subjects
15 measurement occasions (no mistimed measurements)
3 treatment groups
Continuous outcome variable but skewed at all occasions in all three groups
Question of interest: Compare mean trajectory over time among the 3 groups
Had lots of missing data with time, but assume missing is at random

Also, does the choice of using baseline measurement as covariate or as part of outcome vector matter when there are large number of repeated measurements, because the effect of baseline can usually decrease over time.

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rftw
rftw
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Continuous outcome variable - Select between GEE and Linear Mixed Models

What are the arguments for and against selecting GEE and Linear Mixed Models when the outcome variable is continuous? Are they any circumstances where one performs better than other?

The data I am modelling has these features:

Randomized trial, 910 subjects
15 measurement occasions (no mistimed measurements)
3 treatment groups
Continuous outcome variable but skewed at all occasions in all three groups
Question of interest: Compare mean trajectory over time among the 3 groups
Had lots of missing data with time, but assume missing is at random

Also, does the choice of using baseline measurement as covariate or as part of outcome vector matter when there are large number of repeated measurements, because the effect of baseline can usually decrease over time.

Thank you