Statistical analysis of non-inferiority via non-zero risk difference in stratified matched-pair studies. (English) Zbl 1146.62092
Summary: A stratified study is often designed for adjusting several independent trials in modern medical research. We consider the problem of non-inferiority tests and sample size determinations for a nonzero risk difference in stratified matched-pair studies, and develop the likelihood ratio and Wald-type weighted statistics for testing a null hypothesis of non-zero risk difference for each stratum in stratified matched-pair studies on the basis of (1) the sample-based method and (2) the constrained maximum likelihood estimation (CMLE) method. Sample size formulae for the above proposed statistics are derived, and several choices of weights for Wald-type weighted statistics are considered. We evaluate the performance of the proposed tests according to type I error rates and empirical powers via simulation studies.
Empirical results show that (1) the likelihood ratio and the Wald-type CMLE test based on harmonic means of the stratum-specific sample size (SSIZE) weight (the Cochran’s test) behave satisfactorily in the sense that their significance levels are much closer to the prespecified nominal level; (2) the likelihood ratio test is better than J. Nam’s [Non-inferiority of new procedure to standard procedure in stratified matched-pair design. Biometrical J. 48, 966–977 (2006)] score test; (3) the sample sizes obtained by using the SSIZE weight are smaller than other weighted statistics in general; (4) the Cochran’s test statistic is generally much better than other weighted statistics with CMLE method. A real example from a clinical laboratory study is used to illustrate the proposed methodologies.
Empirical results show that (1) the likelihood ratio and the Wald-type CMLE test based on harmonic means of the stratum-specific sample size (SSIZE) weight (the Cochran’s test) behave satisfactorily in the sense that their significance levels are much closer to the prespecified nominal level; (2) the likelihood ratio test is better than J. Nam’s [Non-inferiority of new procedure to standard procedure in stratified matched-pair design. Biometrical J. 48, 966–977 (2006)] score test; (3) the sample sizes obtained by using the SSIZE weight are smaller than other weighted statistics in general; (4) the Cochran’s test statistic is generally much better than other weighted statistics with CMLE method. A real example from a clinical laboratory study is used to illustrate the proposed methodologies.
MSC:
| 62P10 | Applications of statistics to biology and medical sciences; meta analysis |
| 62N03 | Testing in survival analysis and censored data |
| 65C05 | Monte Carlo methods |
Keywords:
CMLE method; likelihood ratio test; non-inferiority test; sample size determinations; tablesReferences:
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