Hello! I am interested in creating contingency tables, namely one that would let me find the frequency and proportion of patients with specific risk factors (dyslipidemia, diabetes, obesity, smoking, hypertension). There are 3 dimensions I would like to divide the population into: sex, family history, and number of risk factors. In R, I used the following code:
mytable<-xtabs(~sex+familyhist+numrisk+hypertension,data=mydata) ftable(mytable) a<-ftable(mytable) prop.table(a,1) However, when I conduct the following code: mytable<-xtabs(~sex+familyhist+numrisk+hypertension+diabetes+obesity+smoking+dyslipidemia,data=mydata) Here the table simply considers the additional risk factors as new dimensions, which I do not want. I would like to find a way where the dimensions are sex, family history, and number of risk factors and I am finding the frequency and prevalence for each risk factor (dyslipidemia, diabetes, obesity, smoking, hypertension) in each of these subgroups. The only way to get around this problem I could think of is to create new data frames for each number of risk factor subgroup: numrisk1, numrisk2, numrisk3…where numrisk1 indicates population with 1 risk factor. Then I could calculate the prevalence of each risk factor separately. This approach will take a very long time so I was hoping to ask if anyone knew of a solution to this issue I am having with contingency tables...perhaps a useful R package? Thank you for your help! Jin Choi Masters Student (Epidemiology) McGill University ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
