Create simple life table

# S3 method for matrix
lifetable(x, strata = list(), breaks = c(),
   weights=NULL, confint = FALSE, ...)

 # S3 method for formula
lifetable(x, data=parent.frame(), breaks = c(),
   weights=NULL, confint = FALSE, ...)

Arguments

x

time formula (Surv) or matrix/data.frame with columns time,status or entry,exit,status

strata

strata

breaks

time intervals

weights

weights variable

confint

if TRUE 95% confidence limits are calculated

...

additional arguments to lower level functions

data

data.frame

Author

Klaus K. Holst

Examples

library(timereg)
data(TRACE)

d <- with(TRACE,lifetable(Surv(time,status==9)~sex+vf,breaks=c(0,0.2,0.5,8.5)))
summary(glm(events ~ offset(log(atrisk))+factor(int.end)*vf + sex*vf,
            data=d,poisson))
#> 
#> Call:
#> glm(formula = events ~ offset(log(atrisk)) + factor(int.end) * 
#>     vf + sex * vf, family = poisson, data = d)
#> 
#> Deviance Residuals: 
#>        1         2         3         4         5         6         7         8  
#>  0.13380  -0.23667   0.01018  -0.09903   0.17138  -0.00721   0.26508   0.48346  
#>        9        10        11        12  
#> -0.60278  -0.19841  -0.39283   0.42195  
#> 
#> Coefficients:
#>                        Estimate Std. Error z value Pr(>|z|)    
#> (Intercept)           -0.444337   0.088565  -5.017 5.25e-07 ***
#> factor(int.end)0.5    -1.197746   0.137896  -8.686  < 2e-16 ***
#> factor(int.end)8.5    -1.871838   0.085480 -21.898  < 2e-16 ***
#> vf                     1.830440   0.212178   8.627  < 2e-16 ***
#> sex                   -0.239036   0.071749  -3.332 0.000864 ***
#> factor(int.end)0.5:vf -1.746744   0.534757  -3.266 0.001089 ** 
#> factor(int.end)8.5:vf -1.927748   0.244888  -7.872 3.49e-15 ***
#> vf:sex                 0.009668   0.230970   0.042 0.966613    
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#> (Dispersion parameter for poisson family taken to be 1)
#> 
#>     Null deviance: 653.5540  on 11  degrees of freedom
#> Residual deviance:   1.1523  on  4  degrees of freedom
#> AIC: 79.938
#> 
#> Number of Fisher Scoring iterations: 4
#>