aco1arm {TwoPhaseInd}

A function to estimate parameters in augmented case-only designs, the genotype is ascertained for a random subcohort from the active treatment arm or the placebo arm.

Description

This function estimates parameters of proportional hazards model with gene-treatment interaction. It employs case-cohort estimation incorporating the case-only estimators. The method was published in Dai et al. (2016) Biometrics.

Usage

aco1arm(data, svtime, event, treatment, BaselineMarker, subcohort, esttype = 1, 
augment = 1, extra)

Arguments

data

A data frame used to access the following data.

svtime

A character string of column name, corresponds to one column of the data frame, which is used to store the failure time variable (numeric).

event

A character string of column name, corresponds to one column of the data frame, which is used to store the indicator of failure event (1: failure, 0: not failure).

treatment

A character string of column name, corresponds to one column of the data frame, which is used to store the binary vector of treatment variable (1: treatment, 0: placebo).

BaselineMarker

A character string of column name, corresponds to one column of the data frame, which is used to store a vector of biomarker.

subcohort

A character string of column name, corresponds to one column of the data frame, which is used to store the indicator of sub-cohort (1: sample belong to the sub-cohort, 0: not belong to the sub-cohort)

esttype

The option of estimation methods (1: Self-Prentice estimator, 0: Lin-Ying estimator).

augment

The indicator of whether subcohort was drawn from the active treatment arm (augment=1) or from the placebo arm (augment=0).

extra

A string vector of column name(s), corresponds to more or more column(s) of the data frame, which is/are used to store the extra baseline covariate(s) to be adjusted for in addition to treatment and biomarker.

Details

The function returns estimates of the proportional hazards model, and variance of the estimates. The method was published in Dai et al. (2016) Biometrics.

Value

A list of estimates and variance of the estimates.

Estimate

A data frame of beta(Estimated parameter), stder(Standard error),and pVal(p value)

Covariance

covariance data frame of genotype,treatment,and interaction

Author(s)

James Y. Dai

References

J. Y. Dai, X. C. Zhang,C. Y. Wang, and C. Kooperberg. Augmented case-only designs for randomized clinical trials with failure time endpoints. Biometrics, DOI: 10.1111/biom.12392, 2016.

See Also

aco2arm

Examples

## Load the example data
data(acodata)

## Augmented data in the active arm

rfit1 <- aco1arm(data=acodata,
                 svtime="vacc1_evinf",
                 event="f_evinf",
                 treatment="f_treat",
                 BaselineMarker="fcgr2a.3",
                 subcohort="subcoh",
                 esttype=1,
                 augment=1,
                 extra=c("f_agele30","f_hsv_2","f_ad5gt18","f_crcm","any_drug",
                         "num_male_part_cat","uias","uras")) 

rfit1

## Augmented data in the placebo arm

rfit2 <- aco1arm(data=acodata,
                 svtime="vacc1_evinf",
                 event="f_evinf",
                 treatment="f_treat",
                 BaselineMarker="fcgr2a.3",
                 subcohort="subcoh",
                 esttype=1,
                 augment=0,
                 extra=c("f_agele30","f_hsv_2","f_ad5gt18","f_crcm", 
                         "any_drug","num_male_part_cat","uias","uras")) 
rfit2