Weighted conditional logistic regression for case-time-control study

Usage

CXO_tc_wt(data, exposure, event, Id, tvc = NULL)

Arguments

data: input dataframe
exposure: exposure variable
event: outcome variable
Id: person ID
tvc: time-varying confounder (optional)

Value

    weighted regression object from clogit

Examples

data(casetimecontrols)
ctcfit <- CXO_tc_wt(data=casetimecontrols,exposure=ex,event=Event,Id=Id)
summary(ctcfit)
#> Call:
#> coxph(formula = Surv(rep(1, 56250L), case_period) ~ ex + ex_tc + 
#>     strata(Id) + offset(lw), data = cases_wt, method = "efron")
#> 
#>   n= 56250, number of events= 625 
#> 
#>            coef exp(coef) se(coef)      z Pr(>|z|)    
#> ex1    -0.01725   0.98290  0.16274 -0.106    0.916    
#> ex_tc1  0.44988   1.56812  0.10822  4.157 3.22e-05 ***
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#>        exp(coef) exp(-coef) lower .95 upper .95
#> ex1       0.9829     1.0174    0.7145     1.352
#> ex_tc1    1.5681     0.6377    1.2684     1.939
#> 
#> Concordance= 0.583  (se = 0.01 )
#> Likelihood ratio test= 30.34  on 2 df,   p=3e-07
#> Wald test            = 29.95  on 2 df,   p=3e-07
#> Score (logrank) test = 30.44  on 2 df,   p=2e-07
#>