Re: Association between two variables over time

Posted by Ryan on Jun 19, 2021; 1:12pm
URL: http://spssx-discussion.165.s1.nabble.com/Association-between-two-variables-over-time-tp5740594p5740602.html

Andreas,

This SUGI paper might be helpful:

https://support.sas.com/resources/papers/proceedings/proceedings/sugi29/198-29.pdf

If you decided to use this approach, you’d need to restructure your file in long (vertical) format, fit a multivariate mixed model using the SPSS MIXED procedure, and output the G and R matrices.

Using G and R, you would calculate the variance covariance matrix for the observations, typically denoted as V. 

Recall that: V = Z*G*TRANSPOS(Z) + R

where 

Z = design matrix for the random effects

G = covariance matrix for the random effects

R = covariance matrix for the residual errors

You would then transform the covariance (first off-diagonal element) to a correlation by dividing the covariance by the product of the square root of the variances of the two variables (first two main diagonal elements). 

HTH.

Ryan 

Sent from my iPhone

On Jun 16, 2021, at 5:26 AM, AndreasV <[hidden email]> wrote:

I would like to investigate the association between serial measurements of
two metric outcomes (e.g., two laboratory parameters measures repeatedly
over several years). Depending on the data set, measurements may have been
obtained at the same time points for all subjects (study data) or at
different time points ('real world' data). Moreover, I may or may not have
to perform comparisons between subsets of subjects (defined, e.g., by
different treatments received).

- What is the most appropriate statistical procedure for this, and
- (how) can this be done in SPSS (I use Version 24)?

Thank you very much!

Andreas



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