DTR (version 1.7)

contrast_chr: Function to compare dynamic treatment regimes (DTRs) based on cumulative hazard ratios (CHRs)

Description

This function compares the cumulative hazard functions of dynamic treatment regimes (DTRs) from sequentially randomized clinical trials by calculating the natural logarithms of cumulative hazard ratios (CHRs) and performing the Wald-type tests based on natural logarithms of CHRs as proposed in Tang and Wahed (2013) [Epub ahead of print].

Usage

contrast_chr(est, t = quantile(est$time, 0.75))

Arguments

est

the result of a call to the CHRestimate 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).

Value

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

Details

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

References

Tang X, Wahed AS: Cumulative hazard ratio estimation for treatment regimes in sequentially randomized clinical trials. Statistics in Biosciences, 2013 [Epub ahead of print]

See Also

CHRestimate, CHR.object

Examples

## Not run: 
# data("CHRdata")
# est <- CHRestimate(data=CHRdata, covar="V1")
# contrast_chr(est, t=1.5)## End(Not run)