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Full-Text Articles in Statistics and Probability
Sas Macro: Testing Marginal Homogeneity In Clustered Matched-Pair Data, Zhao Yang
Sas Macro: Testing Marginal Homogeneity In Clustered Matched-Pair Data, Zhao Yang
Zhao (Tony) Yang, Ph.D.
The SAS Macro and simulated data example are used to demonstrate the application of tests for marginal homogeneity in clustered matched-pair data.
R Code: A Non-Iterative Implementation Of Tango's Score Confidence Interval For A Paired Difference Of Proportions, Zhao Yang
Zhao (Tony) Yang, Ph.D.
For matched-pair binary data, a variety of approaches have been proposed for the construction of a confidence interval (CI) for the difference of marginal probabilities between two procedures. The score-based approximate CI has been shown to outperform other asymptotic CIs. Tango’s method provides a score CI by inverting a score test statistic using an iterative procedure. In the developed R code, we propose an efficient non-iterative method with closed-form expression to calculate Tango’s CIs. Examples illustrate the practical application of the new approach.
Generalized Mcnemar's Test For Homogeneity Of The Marginal Distributions, Zhao Yang
Generalized Mcnemar's Test For Homogeneity Of The Marginal Distributions, Zhao Yang
Zhao (Tony) Yang, Ph.D.
In the matched-pairs data, McNemar's test (McNemar, 1947) can be applied only to the case in which there are two possible categories for the outcome. In practice, however, it is possible that the outcomes are classified into multiple categories. Under this situation, the test statistic proposed by Stuart (1955) and Maxwell (1970) is useful; it is actually the generalization of the McNemar's test, commonly referred to as generalized McNemar's or Stuart-Maxwell test. There is no public available SAS program to calculate this statistic, the author has developed a SAS macro (the code is detailed in appendix) to perform this test …