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, numrisk3â€¦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

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