*! version 1.0.7 15dec2022

Title

scct -- Stochastic Curtailment: Clinical trials

Syntax

ssct #t #cp0 #cp1, alpha(#) beta(#) [nst(string)]

Description

Immediate command to compute the Stochastic Curtailment for clinical trials.

The command uses the specified values:

- #t is the percentage of information accrued (0<#t<=100).

- #cp0 is the conditional power(%) under null hypothesis (50<=#cp0<100).

- #cp1 is the conditional power(%) under alternative hypothesis (50<=#cp1<100).

The alpha option receives the alpha risk in % (0<alpha<50). This option is required.

The beta option receives the beta risk in % (0<beta<50). This option is required.

The nst option receives the name of the study to label the output.

You can click here to pop up a dialog or type db scct.

Execute net from http://metodo.uab.cat/stata for install.

It is important to keep the commands updated. Execute adoupdate scct, update to update the scct command.

Execute adoupdate, update to update all the user-written commands.

If you find any bugs or want to suggest any improvements, please send an e-mail to: leam@uab.cat.

Examples

. scct 50 90 90, alpha(5) beta(15)

. scct 60 90 80, alpha(5) beta(10) nst(Study name)

Version

Version 1.0.7 -- 15 December 2022

Authors

JM.Doménech

Programmer: R.Sesma

Laboratori d'Estadística Aplicada

Universitat Autònoma de Barcelona

leam@uab.cat

Vancouver reference

Doménech JM. Stochastic Curtailment, Clinical trials: User-written command scct for Stata [computer program].

V1.0.7. Bellaterra: Universitat Autònoma de Barcelona; 2022.

Available executing from Stata: net from http://metodo.uab.cat/stata

References

Davis BR, Hardy RJ. Data monitoring in clinical trials: the case for stochastic curtailment. J Clin Epidemiol. 1994; 47:1033-42.

Delgado M, Llorca J, Doménech JM. Estudios experimentales. 5ª ed. Barcelona: Signo; 2012.

Moyé LA. Statistical monitoring of clinical trials. Springer: New York, 2006.