Augmentation for Binomial regression based on stratified NPMLE Cif (Aalen-Johansen)

Computes the augmentation term for each individual as well as the sum $$ A = \int_0^t H(u,X) \frac{1}{S^*(u,s)} \frac{1}{G_c(u)} dM_c(u) $$ with $$ H(u,X) = F_1^*(t,s) - F_1^*(u,s) $$ using a KM for $$G_c(t)$$ and a working model for cumulative baseline related to $$F_1^*(t,s)$$ and $$s$$ is strata, $$S^*(t,s) = 1 - F_1^*(t,s) - F_2^*(t,s)$$.

BinAugmentCifstrata(
  formula,
  data = data,
  cause = 1,
  cens.code = 0,
  km = TRUE,
  time = NULL,
  weights = NULL,
  offset = NULL,
  ...
)

Arguments

formula

formula with 'Event', strata model for CIF given by strata, and strataC specifies censoring strata

data

data frame

cause

of interest

cens.code

code of censoring

km

to use Kaplan-Meier

time

of interest

weights

weights for estimating equations

offset

offsets for logistic regression

...

Additional arguments to binreg function.

Details

Standard errors computed under assumption of correct $$G_c(s)$$ model.

Author

Thomas Scheike

Examples

data(bmt)
dcut(bmt,breaks=2) <- ~age 
out1<-BinAugmentCifstrata(Event(time,cause)~platelet+agecat.2+
      strata(platelet,agecat.2),data=bmt,cause=1,time=40)
summary(out1)
#> 
#>    n events
#>  408    157
#> 
#>  408 clusters
#> coeffients:
#>                      Estimate  Std.Err     2.5%    97.5% P-value
#> (Intercept)          -0.50047  0.17043 -0.83450 -0.16643  0.0033
#> platelet             -0.63482  0.23584 -1.09706 -0.17258  0.0071
#> agecat.2(0.203,1.94]  0.53812  0.21185  0.12291  0.95333  0.0111
#> 
#> exp(coeffients):
#>                      Estimate    2.5%  97.5%
#> (Intercept)           0.60625 0.43409 0.8467
#> platelet              0.53003 0.33385 0.8415
#> agecat.2(0.203,1.94]  1.71279 1.13078 2.5943
#> 
#> 

out2<-BinAugmentCifstrata(Event(time,cause)~platelet+agecat.2+
    strata(platelet,agecat.2)+strataC(platelet),data=bmt,cause=1,time=40)
summary(out2)
#> 
#>    n events
#>  408    157
#> 
#>  408 clusters
#> coeffients:
#>                      Estimate  Std.Err     2.5%    97.5% P-value
#> (Intercept)          -0.49984  0.17054 -0.83409 -0.16559  0.0034
#> platelet             -0.63650  0.23627 -1.09958 -0.17342  0.0071
#> agecat.2(0.203,1.94]  0.53709  0.21190  0.12177  0.95242  0.0113
#> 
#> exp(coeffients):
#>                      Estimate    2.5%  97.5%
#> (Intercept)           0.60663 0.43427 0.8474
#> platelet              0.52914 0.33301 0.8408
#> agecat.2(0.203,1.94]  1.71103 1.12949 2.5920
#> 
#>