contrast_wald: Function to compare dynamic treatment regimes (DTRs) using...
In DTR: Estimation and Comparison of Dynamic Treatment Regimes

Description Usage Arguments Details Value References See Also Examples

This function compares the survival estimates at specific time point among dynamic treatment regimes (DTRs) using the Wald-type tests.

1	contrast_wald(est, t = quantile(est$time, 0.75))

`est`	the result of a call to the `LDTestimate` function or `WRSEestimate` function
`t`	a time point of interest. For example, t=5 for the comparisons of survival estimates at 5 years among DTRs. Default t is set to be the 75th percentile of the observed time (i.e. 75th percentile of U).

Two different comparisons are performed:
1) An overall comparison H0: A1B1=A1B2=A2B1=A2B2
2) Pairwise comparisons including H0: A1B1=A1B2, H0: A1B1=A2B1, H0: A1B1=A2B2, H0: A1B2=A2B1, H0: A1B2=A2B2, and H0: A2B1=A2B2

The function returns a data frame with four columns: H0, test statistic, df, and p.

`H0`	the null hypotheses being tested, for example, H0 (t=3) if the comparisons are made at t=3
`test statistic`	the calculated chi-square test statistic
`df`	the degree of freedom
`p`	the resulting p-value

Lunceford JK, Davidian M, Tsiatis AA: Estimation of survival distributions of treatment policies in two-stage randomization designs in clinical trials. Biometrics 58:48-57, 2002
Guo X, Tsiatis AA: A weighted risk set estimator for survival distributions in two-stage randomization designs with censored survival data. Int. J. Biostatistics 1:1-15, 2005

LDTestimate, WRSEestimate, DTR.object

## Not run: 
# LDT estimates
data("LDTdata")
est <- LDTestimate(data=LDTdata)
contrast_wald(est, t=1)

# WRSE estimates
data("WRSEdata")
est <- WRSEestimate(data=WRSEdata)
contrast_wald(est, t=300)

## End(Not run)