LPJSM_binary: LPJSM for snSMART with binary outcomes (3 active treatments or placebo and two dose level)

Description

A joint-stage regression model (LPJSM) is a frequentist modeling approach that incorporates the responses of both stages as repeated measurements for each subject. Generalized estimating equations (GEE) are used to estimate the response rates of each treatment. The marginal response rates for each DTR can also be obtained based on the GEE results.

Usage

LPJSM_binary(data, six = TRUE, DTR = TRUE, ...)
# S3 method for LPJSM_binary
summary(object, ...)
# S3 method for summary.LPJSM_binary
print(x, ...)
# S3 method for LPJSM_binary
print(x, ...)

Value

a list containing

GEE_output: - original output of the GEE (geeglm) model
pi_hat: - estimate of response rate/treatment effect
sd_pi_hat: - standard error of the response rate
pi_DTR_hat: - expected response rate of dynamic treatment regimens (DTRs)
pi_DTR_se: - standard deviation of DTR estimates

Arguments

data: dataset with columns named as treatment_stageI, response_stageI, treatment_stageII and response_stageII
six: if TRUE, will run the six beta model, if FALSE will run the two beta model. Default is six = TRUE
DTR: if TRUE, will also return the expected response rate and its standard error of dynamic treatment regimens
...: optional arguments that are passed to geepack::geeglm() function.
object: object to print
x: object to summarize.

References

Wei, B., Braun, T.M., Tamura, R.N. and Kidwell, K.M., 2018. A Bayesian analysis of small n sequential multiple assignment randomized trials (snSMARTs). Statistics in medicine, 37(26), pp.3723-3732. URL: doi:10.1002/sim.7900

Chao, Y.C., Trachtman, H., Gipson, D.S., Spino, C., Braun, T.M. and Kidwell, K.M., 2020. Dynamic treatment regimens in small n, sequential, multiple assignment, randomized trials: An application in focal segmental glomerulosclerosis. Contemporary clinical trials, 92, p.105989. URL: doi:10.1016/j.cct.2020.105989

Fang, F., Hochstedler, K.A., Tamura, R.N., Braun, T.M. and Kidwell, K.M., 2021. Bayesian methods to compare dose levels with placebo in a small n, sequential, multiple assignment, randomized trial. Statistics in Medicine, 40(4), pp.963-977. URL: doi:10.1002/sim.8813

Examples

Run this code

data <- data_binary

LPJSM_result <- LPJSM_binary(data = data, six = TRUE, DTR = TRUE)

summary(LPJSM_result)