A fiducial approach for testing the non-inferiority of proportion difference in matched-pairs design.

The non-inferiority of one treatment/drug to another is a common and important issue in medical and pharmaceutical fields. This study explored a fiducial approach for testing the non-inferiority of proportion difference in matched-pairs design. Approximate tests constructed using fiducial quantities with a combination of different parameters were proposed. Four simulation studies were employed to compare the performance of fiducial tests by comparing their type I errors and powers. The results showed that fiducial quantities with parameter 0.6 ≤ w 1 ≤ 0.8 performed satisfactorily from small to large samples. Therefore, the fiducial tests could be recommended for practical applications. The recommended fiducial tests might be a competitive alternative to other available tests. Three real data sets were analyzed to illustrate the proposed methods were competitive or even better than other tests.

Recommended confidence intervals for the conditional odds ratio in matched-pairs designs.

There has been limited research on the confidence intervals of the conditional odds ratio in matched-pairs design. This article investigates the interval estimation of the conditional odds ratio. We described several confidence intervals, which are available in some situations, and they can produce different results. We tried to determine which method(s) should be recommended for different situations. We derived four confidence intervals from the delta test, the score test, the inferential model test, and the fiducial test, and employed four exact calculation studies to compare the performances of the four methods, in order to make recommendations for small and moderate-to-large sample sizes. All of the methods are illustrated using a real example. And we offered the recommendations for different situations.

How to use χ2 test correctly——χ2 test for the data of four-fold table collected from the matched pairs design / 四川精神卫生

The purpose of this paper was to introduce the McNemar΄s χ2 test and SAS and R software implementation of four-fold table data collected from the matched pairs design. Firstly， it was proposed that there were three situations for the data of four-fold table of the paired design， namely ①the data of paired design four-fold table with the special "gold standard" was worthy of statistical analysis； ②the data of four-fold table of the paired design without the special "gold standard" was not worthy of statistical analysis； ③the data of four-fold table collected from the matched pairs design with implicit "gold standard" was worthy of statistical analysis. Secondly， taking the "problems and data" in the first case as the object of statistical analysis， SAS and R software were used to analyze the differences， the calculation results were given and explained， and the statistical and professional conclusions were also made.

Wilcoxon's signed-rank statistic: what null hypothesis and why it matters.

In statistical literature, the term 'signed-rank test' (or 'Wilcoxon signed-rank test') has been used to refer to two distinct tests: a test for symmetry of distribution and a test for the median of a symmetric distribution, sharing a common test statistic. To avoid potential ambiguity, we propose to refer to those two tests by different names, as 'test for symmetry based on signed-rank statistic' and 'test for median based on signed-rank statistic', respectively. The utility of such terminological differentiation should become evident through our discussion of how those tests connect and contrast with sign test and one-sample t-test. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.