Hi so I'm interested in calculating HR for the following variables. age, state and sex. Univariate calculation using R survival package for example looks something like this.
coxph( Surv( as.numeric(x[ ,time] ), as.numeric(x[ ,censor]) )~x$state , method="exact", data=x) # if I run this analysis separately I get the following data beta HR (95% CI for HR) wald.test p.value sex -0.16 0.85 (0.62-1.2) 0.91 0.34 Age 0.0098 1 (0.99-1) 1.4 0.25 state 0.36 1.4 (1-2) 4.3 0.038
The thing is, if I run a multivariate analysis I get the following.
coxph( s_obj ~ x$state + x$sex+ as.numeric ( x$age) , method="exact", data=x) coef exp(coef) se(coef) z p x$state 0.404596 1.498696 0.177897 2.274 0.0229 x$sexm -0.153171 0.857983 0.169687 -0.903 0.3667 as.numeric(x$age) 0.011899 1.011970 0.008561 1.390 0.1646 Likelihood ratio , p=0.04906
I'm trying to interpret this data. My hypothesis is that survival should be dependent on both state and sex. A few questions, should I just dummy code state+sex and run a univariate? Does the data above suggest that state alone independent of sex, effect survival? If I want to truly show that survival is dependent on both state and sex, what would be the best way to do this?