Re: [Freesurfer] Effect of continuous time-varying covariate across time in LME models

[Matthieu Vanhoutte]

Dear Freesurfer's experts,

Would anybody have advice concerning my requests in below mail ?

Thanks in advance.

Best regards,
Matthieu

2017-07-01 11:37 GMT+00:00 Matthieu Vanhoutte :

> Dear Freesurfer’s experts,
>
> I would like to test if neuropsychological score across time (continuous
> time-varying covariate) has an effect on metabolism maps. However, I don’t
> manage to understand how to define design matrix and contrast associated to
> assess it with LME models.
>
> I picked up from one former mailing list discussion including Jorge:
>
> *we recommended to order the columns of the design matrix in the following 
> way:
>
> Column 1: the intercept term (which is a column of ones)
>
> Colum 2: the time covariate if it varies across subjects (eg. time from
> baseline)
>
> Column 3-q: any time-varying covariates (eg. training: 0 before training, 1
> after training)
>
> Column q+1-r: the group covariates of interest (eg. a binary variable
> indicating whether or not the subject is a patient), for n groups you will 
> have
> n-1 binary covariates
>
> Column r+1-s: interactions between group covariates with the time-varying
> covariates (only the interesting interactions)
>
> Column s+1-p: any other nuisance time-invariant covariates (eg.
> age-at-baseline, gender, etc...)*
>
>
> 1) If I apply these advices, I would define in Column 3 my
> neuropsychological scores as my time-varying covariate but should I have to
> normalize these scores ?
>
> 2) If I want to correlate my metabolic maps (inputs) with my
> neuropsychological time-varying covariate should I have to define a column
> of interaction between neuropsychological time-varying covariate and (group
> or time) ?
>
> 3) How should I define contrast matrix to assess this effect ?
>
> Thank you for your advices !!
>
> Best regards,
> Matthieu
>
>
>
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[Freesurfer] Effect of continuous time-varying covariate across time in LME models

[Matthieu Vanhoutte]

Dear Freesurfer’s experts,

I would like to test if neuropsychological score across time (continuous 
time-varying covariate) has an effect on metabolism maps. However, I don’t 
manage to understand how to define design matrix and contrast associated to 
assess it with LME models.

I picked up from one former mailing list discussion including Jorge:
we recommended to order the columns of the design matrix in the following way:

Column 1: the intercept term (which is a column of ones)

Colum 2: the time covariate if it varies across subjects (eg. time from 
baseline)

Column 3-q: any time-varying covariates (eg. training: 0 before training, 1 
after training)

Column q+1-r: the group covariates of interest (eg. a binary variable 
indicating whether or not the subject is a patient), for n groups you will have 
n-1 binary covariates

Column r+1-s: interactions between group covariates with the time-varying 
covariates (only the interesting interactions)

Column s+1-p: any other nuisance time-invariant covariates (eg. 
age-at-baseline, gender, etc...)

1) If I apply these advices, I would define in Column 3 my neuropsychological 
scores as my time-varying covariate but should I have to normalize these scores 
?

2) If I want to correlate my metabolic maps (inputs) with my neuropsychological 
time-varying covariate should I have to define a column of interaction between 
neuropsychological time-varying covariate and (group or time) ?

3) How should I define contrast matrix to assess this effect ?

Thank you for your advices !!

Best regards,
Matthieu


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Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer


The information in this e-mail is intended only for the person to whom it is
addressed. If you believe this e-mail was sent to you in error and the e-mail
contains patient information, please contact the Partners Compliance HelpLine at
http://www.partners.org/complianceline . If the e-mail was sent to you in error
but does not contain patient information, please contact the sender and properly
dispose of the e-mail.