My attempt is to define a survival analysis model from a case-cohort study, where a subcohort is initially selected randomly. Later on, all cases from the entire cohort are added non-randomly to the subcohort. In my case, the goal is to estimate whether molecules measured in blood could serve as biomarkers for cardiovascular disease. I am working with the survival package in R, specifically using the cch function. I have observed random effects in classical Cox regression models here , here
The issue arises from the experimental analysis, where the dendrogram revealed an anomaly in one specific batch, requiring further adjustment. Until now, I have primarily worked with longitudinal models, which have allowed me to determine and specify random effects.
I am curious if it's possible to incorporate random effects into Cox regression, particularly using the cch function. While exploring information on Cross-Validated, I found limited threads discussing cch. I haven't found though, an argument contained in the function letting random effects to be included Conceptually, if I'm artificially or voluntarily adding cases to the subcohort, would it be appropriate to determine random effects? From my understanding, this is not a random occurrence, but rather a specific effect to be determined.
If not possible to include it as random effect, do you think is plausible to include it as covariable, considering just the subcohort size of 240 and proven batch effect around 10 samples
The model I attempt to execute:
# The model without batch or box effect being
# tocoro: time to event or censoring
# iam: event (acute infarction)
# edat: age
# sexe: sex
# hsamir985p: covariate of interest
Surv(tocoro, iam) ~ edat + sexe + hsamir985p
Including the box
Surv(tocoro, iam) ~ edat + sexe + hsamir985p + box
Edit1:
From the hierarchical analysis done to establish if there are different clusters according batch or box, the results showed one box with lower quality of DNA was clustered apart. I refer to hsamir985p among other biomarkers, but yes. This batch or box effect is what I am trying to smooth. Not sure what you refer to make them comparable? To establish like a regression and then include the results from problematic box?? Regarding cases and controls, I have 194 and 52
