Biomaterial Database

A new procedure for group sequential analysis in clinical trials. 1992

B Falissard, and J Lellouch

INSERM U 169, Villejuif, France.

Since Pocock (1977, Biometrika 64, 191-199), many methods have been developed for group sequential analysis of clinical trials. However, these methods remain underemployed partly because of inconsistencies of sequential testing [Berry (1987, The Statistician 36, 181-189)]. This paper considers a new approach, which, by requiring that a succession of interim analyses be significant at the alpha level, both preserves the overall significance level alpha and does not present some of the inconsistencies of the previous methods. Results are obtained for a normal or binary response and for survival data. A comparison with the usual group sequential testing is also presented.

UI	MeSH Term	Description	Entries
D008433	Mathematics	The deductive study of shape, quantity, and dependence. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 6th ed)	Mathematic
D011336	Probability	The study of chance processes or the relative frequency characterizing a chance process.	Probabilities
D011897	Random Allocation	A process involving chance used in therapeutic trials or other research endeavor for allocating experimental subjects, human or animal, between treatment and control groups, or among treatment groups. It may also apply to experiments on inanimate objects.	Randomization,Allocation, Random
D002986	Clinical Trials as Topic	Works about pre-planned studies of the safety, efficacy, or optimum dosage schedule (if appropriate) of one or more diagnostic, therapeutic, or prophylactic drugs, devices, or techniques selected according to predetermined criteria of eligibility and observed for predefined evidence of favorable and unfavorable effects. This concept includes clinical trials conducted both in the U.S. and in other countries.	Clinical Trial as Topic
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000704	Analysis of Variance	A statistical technique that isolates and assesses the contributions of categorical independent variables to variation in the mean of a continuous dependent variable.	ANOVA,Analysis, Variance,Variance Analysis,Analyses, Variance,Variance Analyses
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model