scholarly journals SEQUENTIAL DATA WEIGHTING PROCEDURES FOR COMBINED RATIO ESTIMATORS IN COMPLEX SAMPLE SURVEYS

2017 ◽  
Vol 18 (2) ◽  
pp. 247-270
Author(s):  
Aylin Alkaya ◽  
H. Öztaş Ayhan ◽  
Alptekin Esin
Keyword(s):  
Sequential Data ◽  
Sample Surveys ◽  
Data Weighting ◽  
Complex Sample ◽  
Ratio Estimators ◽  
Weighting Procedures

Joint modeling of medical cost and survival in complex sample surveys

2012 ◽  
Vol 32 (9) ◽  
pp. 1509-1523 ◽  
Author(s):  
Huiping Xu ◽  
Joanne Daggy ◽  
Danni Yu ◽  
Bruce A. Craig ◽  
Laura Sands
Keyword(s):  
Medical Cost ◽  
Joint Modeling ◽  
Sample Surveys ◽  
Complex Sample

New alternatives to ratio estimators of population variance in sample surveys

2014 ◽  
Vol 247 ◽  
pp. 255-265
Author(s):  
Hilal A. Lone ◽  
Rajesh Tailor ◽  
Housila P. Singh ◽  
Med Ram Verma
Keyword(s):  
Sample Surveys ◽  
Population Variance ◽  
Ratio Estimators

scholarly journals ReGenesees: an Advanced R System for Calibration, Estimation and Sampling Error Assessment in Complex Sample Surveys

2015 ◽  
Vol 31 (2) ◽  
pp. 177-203 ◽  
Author(s):  
Diego Zardetto
Keyword(s):  
Variance Estimation ◽  
Sampling Error ◽  
Mathematical Function ◽  
Sample Surveys ◽  
Symbolic Information ◽  
Strong Point ◽  
Complex Sample ◽  
R Programming ◽  
The Right ◽  
Assisted Analysis

Abstract ReGenesees is a new software system for design-based and model-assisted analysis of complex sample surveys, based on R. As compared to traditional estimation platforms, it ensures easier and safer usage and achieves a dramatic reduction in user workload for both the calibration and the variance estimation tasks. Indeed, ReGenesees allows the specification of calibration models in a symbolic way, using R model formulae. Driven by this symbolic metadata, the system automatically and transparently generates the right values and formats for the auxiliary variables at the sample level, and assists the user in defining and calculating the corresponding population totals. Moreover, ReGenesees can handle arbitrary complex estimators, provided they can be expressed as differentiable functions of Horvitz-Thompson or calibration estimators of totals. Complex estimators can be defined in a completely free fashion: the user only needs to provide the system with the symbolic expression of the estimator as a mathematical function. ReGenesees is in fact able to automatically linearize such complex estimators, so that the estimation of their variance comes at no cost at all to the user. Remarkably, all the innovative features sketched above leverage a particular strong point of the R programming language, namely its ability to process symbolic information.

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