I need some help/advice for tackling the following problem:
The investigators I'm working with are interested in investigating the association between various covariates and the reason for termination from a kidney disease data registry. The hypothesis is that a lower proportion of ethnic/racial minorities will get kidney transplant rather than dialysis at time of end stage kidney disease onset (i.e., time of termination from registry).
Outcome: reason for termination (the dataset has this as a categorical variable with numerous categories which I narrowed down to only 4 categories: transplant, dialysis, death, other. The "other" category is the most numerous as it contains everybody terminated for any reason other than transplant/dialysis/death, plus over 300 cases who had missing value for reason for termination (these patients might still be in the registry for all we know, there's no way of knowing what happened with them), followed by transplant, dialysis and death (just a couple of cases of death).
Covariates: some are time-independent (sex, race/ethnicity) while others are measured repeatedly at 6-months visits so time-dependent (such as lab values, hypertension status, eGFR).
My initial thoughts for analysis:
A. repeated measures multinomial logistic regression analysis, given the outcome with more than 2 categories, and the time-dependent nature of some of the covariates, or
B. repeated measures competing risks/cause-specific hazards analysis
The challenges:
Can somebody please help advise what the appropriate type of analysis would be given the study context/research hypothesis?
Thank you kindly!
Thank you for the suggestions! It seems that this would be a two-step process with PROC LOGISTIC. I was wondering though, would it be possible to maybe use PROC GLIMMIX instead with GLOGIT link? Do you know of any good references/tutorials that might illustrate how to implement this for similar problems?
Thank you again!
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