Complex Survey Data Analysis with SAS

Simplifying the Analysis of Complex Survey Data Using the SAS

Large sample-based surveys often have complex sample designs, with design features including stratification, clustering, multi-stage sampling, and unequal probability of selection of observations. The calculation of the associated sampling weights often involves nonresponse adjustments and raking to external control totals. The analysis usually includes descriptive statistics such as frequencie...

Resampling Methods in Complex Survey Data

Small Area Estimation for Survey Data Analysis Using SAS® Software

Small area estimation is important in survey analysis when domain (subpopulation) sample sizes are too small to provide adequate precision for direct domain estimators. Popular techniques for small area estimation use implicit or explicit statistical models to indirectly estimate the small area parameters of interest. Indirect estimation requires you to go beyond the survey data analysis method...

Complex-Valued Data Envelopment Analysis

Data Envelopment Analysis (DEA) is a nonparametric approach for measuring the relative efficiency of a decision making units consists of multiple inputs and outputs. In all standard DEA models semi positive real valued measures are assumed, while in some real cases inputs and outputs may take complex valued. The question is related to measuring efficiency in such cases. As far as we are aware, ...

Analysis of Survival Data with Recurrent Events Using SAS ®

This paper presents the application of survival analysis methods using SAS/STAT ® to a large clinical trial, which was designed to test the treatment effect on preventing recurrent stroke and cardiovascular events. In this paper, we present the complete analysis procedure of this case study, including the model assumption check, model selection, and the utility and discussion on the Cox proport...