succ_ia_betabinom_one {LongCART}

Determines predictive power of success based on interim results and beta prior for one-sample binary data

Description

This function can be used to determine predictive power for trial success and clinical success based on the interim results and beta prior distribution for test of population proportion.

Usage

succ_ia_betabinom_one(N, n, x, 
                      null.value = 0, alternative = "greater", 
                      test="z", correct=TRUE,
                      succ.crit = "trial", Z.crit.final = 1.96, 
                      alpha.final = 0.025, clin.succ.threshold = NULL, 
                      a = 1, b = 1)

Arguments

N

Sample size at final analysis. Cannot be missing.

n

Sample size at interim analysis. Cannot be missing.

x

Number of observed response at interim analysis. Cannot be missing.

null.value

The specified value under null hypothesis. Default is 0.

alternative

Direction of alternate hypothesis. Can be "greater" or "less".

test

Statistical test. Default is "z" for Z test. For Exact binomial test, specify "exact".

correct

A logical indicating whether Yates' continuity correction should be applied where possible. Applies to approximate Z-test only.

succ.crit

Specify "trial" for trial success (i.e., null hypothesis is rejected at final analysis) or "clinical" for clinical success (i.e., estimated value at the final analysis is greater than clinically meaningful value as specified under clin.succ.threshold.)

Z.crit.final

The rejection boundary at final analysis in Z-value scale. Either alpha.final or Z.crit.final must be specified when determining trial success.

alpha.final

The rejection boundary at final analysis in alpha (1-sided) scale (e.g., 0.025). Either alpha.final or Z.crit.final must be specified when determining trial success.

clin.succ.threshold

Clinically meaningful value. Required when succ.crit="clinical".

a

Value of a corresponding to Beta(a, b) prior for proportion.

b

Value of b corresponding to Beta(a, b) prior for proportion.

Details

This function can be used to determine Predictive power or predictive probability of success (PPoS) based on the interim results for testing of population proportion. The calculation of PoS is carried out assuming beta prior distributions for proportion. This function can be used to determine clinical success (succ.crit="clinical") and trial success (succ.crit="trial"). For clinical success, clin.succ.threshold must be specified. For trial success, Z.crit.final or alpha.final must be specified.

Author(s)

Madan Gopal Kundu <[e-mail]>

References

Kundu, M. G., Samanta, S., and Mondal, S. (2021). An introduction to the determination of the probability of a successful trial: Frequentist and Bayesian approaches. arXiv preprint arXiv:2102.13550.

See Also

succ_ia_betabinom_two, succ_ia, PoS

Examples

succ_ia_betabinom_one( N=40, n=30, x=25, 
        null.value=0.6, alternative="greater", 
        succ.crit = "trial", alpha.final = 0.016,  
        a = 1, b=1) 

succ_ia_betabinom_one( N=40, n=30, x=25, 
        null.value=0.6, alternative="greater", test="exact",
        succ.crit = "trial", alpha.final = 0.016,  
        a = 1, b=1) 

succ_ia_betabinom_one( N=40, n=30, x=15, 
        null.value=0.6, alternative="greater", 
        succ.crit = "clinical", clin.succ.threshold =0.5,  
        a = 1, b=1)