Hi all β thanks so much for the great forum and data. Novice question here.
I am trying to recreate the analyses shown here: Heterogeneity among women with stroke: health, demographic and healthcare utilization differentials - PMC
Specifically:
Second, the correlation between healthcare utilization, demographic/lifestyle traits and health status and prevalence of stroke was calculated for the young and old cohorts of women using Cox proportional hazards regression on a match cohort of young and old women with and without stroke. Matching was performed using propensity scores derived from age, race, region of residence, education, household size, and marital status with replacement.
I am seeking to do a very similar analysis with a different subsetted population. Iβve performed the propensity score matching in R using the MatchIt package, e.g.,
Hisp.Matched <- matchit(Match~AGE + Black + REGION + FAMSIZE + Married, data=Hisp_Match2, method = 'nearest', ratio = 1, replace = TRUE)
With Hisp_Match2 being the subsetted data free of NAs/βMatchβ as the column separating the individuals WITH the diagnosis from those WITHOUT the diagnosis. Unsure of how to proceed without a time variable, though.
Thanks for any and all help!