succ_ia_betabinom_one | R Documentation |
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.
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)
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 |
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 |
Z.crit.final |
The rejection boundary at final analysis in Z-value scale. Either |
alpha.final |
The rejection boundary at final analysis in alpha (1-sided) scale (e.g., 0.025). Either |
clin.succ.threshold |
Clinically meaningful value. Required when |
a |
Value of |
b |
Value of |
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.
Madan Gopal Kundu <madan_g.kundu@yahoo.com>
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.
succ_ia_betabinom_two
, succ_ia
, PoS
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)
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