Open Access. Powered by Scholars. Published by Universities.®

Statistics and Probability Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 5 of 5

Full-Text Articles in Statistics and Probability

Sas Macro: Testing Marginal Homogeneity In Clustered Matched-Pair Data, Zhao Yang Jan 2014

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.


Sas Macro: Weighted Kappa Statistic For Clustered Matched-Pair Ordinal Data, Zhao Yang Jan 2014

Sas Macro: Weighted Kappa Statistic For Clustered Matched-Pair Ordinal Data, Zhao Yang

Zhao (Tony) Yang, Ph.D.

This SAS macro calculate the weighted kappa statistic and its corresponding non-parametric variance estimator for the clustered matched-pair ordinal data.


Sas Macro: Kappa Statistic For Clustered Physician-Patients Polytomous Data, Zhao Yang Jan 2014

Sas Macro: Kappa Statistic For Clustered Physician-Patients Polytomous Data, Zhao Yang

Zhao (Tony) Yang, Ph.D.

This SAS macro calculate the kappa statistic and its semi-parametric variance estimator for the clustered physician-patients polytomous data. The proposed method depends on the assumption of conditional independence for the clustered physician-patients data structure.


Sas Macro: Kappa Statistic For Clustered Matched-Pair Data, Zhao Yang Jan 2013

Sas Macro: Kappa Statistic For Clustered Matched-Pair Data, Zhao Yang

Zhao (Tony) Yang, Ph.D.

The SAS macro was developed to calculate the kappa statistic for the clustered matched-pair data.


R Code: A Non-Iterative Implementation Of Tango's Score Confidence Interval For A Paired Difference Of Proportions, Zhao Yang Jan 2012

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.