Premium
Sample Size Determination for Grouped Exponential Observations: A Cost Function Approach
Author(s) -
Lui KungJong,
Steffey Duane,
Pugh Jamie K.
Publication year - 1993
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710350605
Subject(s) - statistics , sample size determination , censoring (clinical trials) , mathematics , sample (material) , power function , interval (graph theory) , exponential distribution , type i and type ii errors , econometrics , exponential function , mathematical analysis , chemistry , chromatography , combinatorics
Calculating the required sample size for a desired power at a given type I error level, we often assume that we know the exact time of all subject responses whenever they occur during our study period. It is very common, however, in practice that we only monitor subjects periodically and, therefore, we know only whether responses occur or not during an interval. This paper includes a quantitative discussion of the effect resulting from data grouping or interval censoring on the required sample size when we have two treatment groups. Furthermore, with the goal of exploring the optimum in the number of subjects, the number of examinations per subject for test responses, and the total length of a study time period, this paper also provides a general guideline about how to determine these to minimize the total cost of a study for a desired power at a given α‐level. A specified linear cost function that incorporates the costs of obtaining subjects, periodic examinations for test responses of subjects, and the total length of a study period, is assumed, primarily for illustrative purpose.