A SAS MACRO FOR LOGLINEAR SMOOTHING: APPLICATIONS AND IMPLICATIONS

Using PROC GENMOD for Loglinear Smoothing

AND INTRODUCTION The goal of smoothing is to replace an observed frequency distribution with a distribution that preserves some features of the observed data without the irregularities that are attributable to sampling. The type of smoothing covered in this paper involves the fitting of loglinear, Poisson-based models to discrete distributions. Loglinear smoothing can preserve a variety of diff...

%QLS SAS® Macro: A SAS Macro for Analysis of Longitudinal Data Using Quasi- Least Squares

Quasi-least squares (QLS) is an alternative computational approach for estimation of the correlation parameter in the framework of generalized estimating equations (GEE). QLS allows for easier implementation of some correlation structures that are not available for GEE. We describe a user-written SAS® macro called %QLS, and demonstrate application of our macro using a clinical trial example for...

A SAS Macro for Theil Regression

SAS Macro Version Control

During the development and maintenance (life-cycle) process of SAS® macros, especially while they are already used for production purposes, it is very much recommended to keep a history of changes, additions and bug fixes along with the macro version number. Archiving of the production SAS program code should include the applied macro version or at least the applied macro version number. That w...

A SAS macro for parametric and semiparametric mixture cure models

Cure models have been developed to analyze failure time data with a cured fraction. For such data, standard survival models are usually not appropriate because they do not account for the possibility of cure. Mixture cure models assume that the studied population is a mixture of susceptible individuals, who may experience the event of interest, and non-susceptible individuals that will never ex...