A maximum test in lieu of forcing a choice between the two dependent samples t-test and Wilcoxon signed-ranks test is proposed. The maximum test, which requires a new table of critical values, maintains nominal α whi...A maximum test in lieu of forcing a choice between the two dependent samples t-test and Wilcoxon signed-ranks test is proposed. The maximum test, which requires a new table of critical values, maintains nominal α while guaranteeing the maximum power of the two constituent tests. Critical values, obtained via Monte Carlo methods, are uniformly smaller than the Bonferroni-Dunn adjustment, giving it power superiority when testing for treatment alternatives of shift in location parameter when data are sampled from non-normal distributions.展开更多
We propose a new nonparametric test based on the rank difference between the paired sample for testing the equality of the marginal distributions from a bivariate distribution. We also consider a modification of the n...We propose a new nonparametric test based on the rank difference between the paired sample for testing the equality of the marginal distributions from a bivariate distribution. We also consider a modification of the novel nonparametric test based on the test proposed by Baumgartern, Weiβ, and Schindler (1998). An extensive numerical power comparison for various parametric and nonparametric tests was conducted under a wide range of bivariate distributions for small sample sizes. The two new nonparametric tests have comparable power to the paired t test for the data simulated from bivariate normal distributions, and are generally more powerful than the paired t test and other commonly used nonparametric tests in several important bivariate distributions.展开更多
Objective This paper propses a family of summary chi square tests for comparing survival rates at all points of time between two groups. Methods They are respectively derived from the Peto et al. expression for the lo...Objective This paper propses a family of summary chi square tests for comparing survival rates at all points of time between two groups. Methods They are respectively derived from the Peto et al. expression for the log rank test, the Mantel Haenszel expression for the log rank test, and the generalized Wilcoxon test by means of using the homogenetic effective sample size in place of the number at risk and using the corresponding numerator of the conditional probability surviving in place of the death number. Results After such derivations they become clearer in clinical significance, more powerful, and free from the assumption of proportional hazard. Conclusion These tests can be employed in analyzing the clinical data of cancer. A worked example illustrates the methodology.展开更多
文摘A maximum test in lieu of forcing a choice between the two dependent samples t-test and Wilcoxon signed-ranks test is proposed. The maximum test, which requires a new table of critical values, maintains nominal α while guaranteeing the maximum power of the two constituent tests. Critical values, obtained via Monte Carlo methods, are uniformly smaller than the Bonferroni-Dunn adjustment, giving it power superiority when testing for treatment alternatives of shift in location parameter when data are sampled from non-normal distributions.
文摘We propose a new nonparametric test based on the rank difference between the paired sample for testing the equality of the marginal distributions from a bivariate distribution. We also consider a modification of the novel nonparametric test based on the test proposed by Baumgartern, Weiβ, and Schindler (1998). An extensive numerical power comparison for various parametric and nonparametric tests was conducted under a wide range of bivariate distributions for small sample sizes. The two new nonparametric tests have comparable power to the paired t test for the data simulated from bivariate normal distributions, and are generally more powerful than the paired t test and other commonly used nonparametric tests in several important bivariate distributions.
文摘Objective This paper propses a family of summary chi square tests for comparing survival rates at all points of time between two groups. Methods They are respectively derived from the Peto et al. expression for the log rank test, the Mantel Haenszel expression for the log rank test, and the generalized Wilcoxon test by means of using the homogenetic effective sample size in place of the number at risk and using the corresponding numerator of the conditional probability surviving in place of the death number. Results After such derivations they become clearer in clinical significance, more powerful, and free from the assumption of proportional hazard. Conclusion These tests can be employed in analyzing the clinical data of cancer. A worked example illustrates the methodology.
