Applied Survey Data Analysis

Site Overview

This site contains information about the text "Applied Survey Data Analysis", (first and second editions) including author biographies,links to public release data sets and related sites, code and output for analysis examples replicated in current software packages, and information about new publications of interest to survey data analysts. Other features include a FAQ log and links to other software and statistical sites. We plan to intermittently update this site with news about ongoing statistical and software advances in the field of analysis of survey data.

Special Notes from Authors

ASDA-Second Edition is Available as of June 28, 2017!

Project Overview

Applied Survey Data Analysis is the product born of many years of teaching applied survey data analysis classes and practical experience analyzing survey data. We have taught various versions of this course in the ISR/SRC Summer Institute Program, as part of University of Michigan/CSCAR, and within the Survey Methodology Program at University of Michigan and University of Maryland. Our goal has been to integrate teaching materials and practical analysis knowledge into a textbook geared to a level accessible for graduate students and working analysts who may have varying levels of statistical and analytic expertise. We intend to update the materials on this website as statistical and software improvements emerge with the goal of assisting analyst and researchers performing survey data analysis.

Information About Authors

Patricia A. Berglund is a Senior Research Associate in the Survey Methodology Program at the Institute for Social Research. She has extensive experience in the use of computing systems for data management and complex sample survey data analysis. She works on research projects in youth substance abuse, adult mental health, and survey methodology using data from Army STARRS, Monitoring the Future, the National Comorbidity Surveys, World Mental Health Surveys, Collaborative Psychiatric Epidemiology Surveys, and various other national and international surveys. In addition, she is involved in development, implementation, and teaching of analysis courses and computer training programs at the Survey Research Center-Institute for Social Research. She previously lectured in the SAS Institute-Business Knowledge Series. mailto:pberg@umich.edu

Steven G. Heeringa is a Research Scientist in the Survey Methodology Program, the Director of the Statistical and Research Design Group in the Survey Research Center, and the Director of the Summer Institute in Survey Research Techniques at the Institute for Social Research. He has over 25 years of statistical sampling experience directing the development of the SRC National Sample design, as well as sample designs for SRC's major longitudinal and cross-sectional survey programs. During this period he has been actively involved in research and publication on sample design methods and procedures such as weighting, variance estimation, and the imputation of missing data that are required in the analysis of sample survey data. He has been a teacher of survey sampling methods to U.S. and international students and has served as a sample design consultant to a wide variety of international research programs based in countries such as Russia, the Ukraine, Uzbekistan, Kazakhstan, India, Nepal, China, Egypt, Iran, and Chile. mailto:sheering@umich.edu

Brady T. West is a Research Professor in the Survey Methodology Program, located within the Survey Research Center at the Institute for Social Research on the University of Michigan-Ann Arbor (U-M) campus. He earned his PhD from the Michigan Program in Survey and Data Science in 2011. Before that, he received an MA in Applied Statistics from the U-M Statistics Department in 2002, being recognized as an Outstanding First-year Applied Masters student, and a BS in Statistics with Highest Honors and Highest Distinction from the U-M Statistics Department in 2001. His current research interests include responsive and adaptive survey design, the implications of measurement error in auxiliary variables and survey paradata for survey estimation, selection bias in surveys, interviewer effects, and multilevel regression models for clustered and longitudinal data. He is the lead author of a book comparing different statistical software packages in terms of their mixed-effects modeling procedures (Linear Mixed Models: A Practical Guide using Statistical Software, Third Edition, Chapman Hall/CRC Press, 2022). He was elected as a Fellow of the American Statistical Association in 2022. Brady lives in Dexter, MI with his wife Laura, his son Carter, and his daughter Everleigh. mailto:bwest@umich.edu

Professional Reviews of ASDA-Second Edition

Review/Summary from Chapman Hall Website

Features
- Bootstrap methods of variance estimation.

- Estimation and inference for specialized functions such as the Gini coefficient and log-linear models.

- Updated approaches to examining model diagnostics, testing goodness of fit, and estimation and display of marginal effects in linear and generalized linear models.

- State-of-the-art methods for analysis of longitudinal survey data.

- Fractional imputation methods for item missing data.

- Enhanced treatment of methods and software for fitting multilevel models, structural equation models and other latent variable models to complex sample survey data.

- Updated review of software packages for the analysis of complex sample survey data.
Summary
Highly recommended by the Journal of Official Statistics, The American Statistician, and other journals, Applied Survey Data Analysis, Second Edition provides an up-to-date overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first edition, this second edition expands the topics covered and presents more step-by-step examples of modern approaches to the analysis of survey data using the newest statistical software.

Designed for readers working in a wide array of disciplines who use survey data in their work, this book continues to provide a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. An example-driven guide to the applied statistical analysis and interpretation of survey data, the second edition contains many new examples and practical exercises based on recent versions of real-world survey data sets. Although the authors continue to use Stata for most examples in the text, they also continue to offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s updated Web site.

Links to Data Sets for First and Second Editions

National Comorbidity Survey-Replication (Collaborative Psychiatric Epidemiology Surveys)

https://www.hcp.med.harvard.edu/ncs (for NCS-R specific information)

National Health and Nutrition Examination Survey (National Center for Health Statistics)

        https://www.cdc.gov/nchs/

Health and Retirement Survey (Institute for Social Research-University of Michigan)

        https://hrsonline.isr.umich.edu

European Social Survey (ESS)

        https://www.europeansocialsurvey.org/

United States Census Bureau

     https://www.census.gov/

Chapter Exercises Data Sets - Second Edition

   These data sets are subsets of the original data and are designed for use with the chapter exercises in ASDA Second Edition. We provide SAS and Stata format data sets here but for other software, please use a data transfer software or import/export tools within software of choice to translate to needed format.
If you receive a warning about zip files not safe to download, please ignore it!
     Chapter Exercises Data Sets (SAS Format) - Second Edition      Chapter Exercises Data Sets (Stata Format) - Second Edition

Chapter Exercises Data Sets - First Edition

     These data sets are subsets of the original data and are designed for use with the chapter exercises in ASDA.

      Chapter Exercises Data Sets (Stata and SAS Format) - First Edition     Chapter Exercises Data Sets (R Format) - First Edition

Analysis Example Data Sets - First Edition

     These data sets are subsets of the original data and are designed for use with the analysis examples in ASDA - First Edition. We have included the raw variables used in the variable recodes and constructed variables used in the analysis examples.

      Analysis Examples Data Sets (Stata and SAS Format) - First Edition

Frequently Asked Questions

        This document contains frequently asked questions and brief answers. Click here: FAQ Document

        This working paper addresses Accounting for Multi-stage Sample Designs in Complex Sample Variance Estimation by Brady West. Click here to download: Multi-Stage Sample Designs

Links to Additional Sites

Data Archive

        University of Michigan (ICPSR) Data Archive https://www.icpsr.umich.edu

Software for Survey Data Analysis

        SAS software     https://www.sas.com

        STATA software     https://www.stata.com

        Sudaan software     https://www.rti.org

        SPSS software     http://www.spss.com

        Mplus software     https://statmodel.com

        R software     https://www.r-project.org/

        WesVar software     https://www.westat.com/capability/information-technology/wesvar

        IVEware     iveware.org

        SDA from ICPSR https://www.icpsr.umich.edu (online analysis system with survey correction capabilities)
        Manual for Package "svydiags" from R, Linear Regression Model Diagnostics for Survey Data Link to Manual

Software Updates

Stata - V14 is current as of May 2017

IBM/SPSS-SPSS 22 is current as of May 2017

SAS - v9.4 is current as of May 2017

See software websites for additional software updates and versions

Supplemental Code

This section provides key updates to software for analysis of survey data.

SAS-Example of how to use replicate weights using NHANES data: SAS Replicate Weights Example

Stata-Example of Mediation analysis with survey data and subpopulation indicator: Stata sgmediation example

R-Example of Quantile Regression with Bootstrap Method: R Quantile Regression Example

SAS-Example of use of NOMCAR option with PROC SURVEYMEANS: SAS NOMCAR Example

Example of How to Create a Delimited Text File in SAS and Read Text File in R: Text File SAS to R Example

An Example of Fullers (1984) Method for Testing the Bias of Unweighted Estimates of Regression Parameters in a Linear Regression Model: Fuller's Method

SAS code to implement Wilcoxon rank sum test for complex sample survey data: https://www.blackwellpublishing.com/rss

SAS Paper with Examples of ODS Graphics and SG Procedures with Examples of Weighted Frequency Plots: SAS Paper with ODS Graphics and SG Procedures Examples

Note on How SPSS handles Strata with A Single or "Lonely" PSU: https://www-01.ibm.com/support/docview.wss?uid=swg21479202

Link to Stata command for calculation of Population Attributable Risk proportions (user written "punaf" command): https://www.imperial.ac.uk/nhli/r.newson/usergp/uk2012/newson_ohp1.pdf

Example of using PROC EXPORT to convert SAS data set to Stata (.dta) and SPSS (.sav): SAS PROC EXPORT Example

Multiple Imputation Using the Fully Conditional Specification Method: A Comparison of SAS, Stata, IVEware, and R: Link to Presentation

Analysis of Survey Data Using the SAS SURVEY Procedures: A Primer: Link to Presentation

Link to Web Site with Information about Free Tools for Survey Data Analysis and Map Production: https://www.asdfree.com/2014/12/maps-and-art-of-survey-weighted.htm Link to full code for Map Examples: https://github.com/davidbrae/swmap

SAS Repeated Replication Macro to do Design-Based Poisson Regression (with a comparison to Stata svy: poisson command): Link to Code and Results

New Stata V14+ Features: 1.The "survwgt" contributed package for creating replicate weights: Link to Package. 2.The "bs4rw" modifier for performing quantile regression. Install using https://www.stata.com/users/jpitblado/bs4rw. Implement a command referring to replicate weights that have already been generated: "survwgt: bs4rw, rw(brrrwt*): qreg $depvar $demo if subpop==1 [pw=perwt5], q(.5)".

R package for fractional hot deck imputation (FHDI) is now available from CRAN (Primary Author, Dr. Jae Kim). Link to Code and Information

Modified Stata file, pwigls_genlin_adcv_modAV1.do for C11 for Viega Method (Author is Dr. A. Viega). Link to File

Example of SAS 9.4 PROC SURVEYMEANS with DOMAIN Statement and DIFF Option for Difference of Means Test. Link to File

Example of Use of R "Convey" Package for Svy GINI Coefficient. Link to File

Examples of R Survey Package RegTermTest Command Syntax For Tests of Interactions Only and Main Effects Plus Interactions. Link to File

Information and Link to R svydiags package for Survey Regression Diagnostics by Dr. Valliant. This work contains functions for computing diagnostics for fixed effects linear regression models fitted with survey data. Extensions of standard diagnostics to complex survey data are included: standardized residuals, leverages, Cook's D, dfbetas, dffits, condition indexes, and variance inflation factors. Link to CRAN

Example of Stata v16 Lincom Command. The latest syntax is included in this example. Note that this is different than previous Stata versions. Link to Example

Slides and R/STAN code from Presentation "Pseudo-Bayesian Inference for Complex Survey Data", April 2020, Matt Williams and Terrance Savitsky. Link to Slides Link to R/STAN Code

Discussion of R Packages for Survey Data Analysis "srvyr compared to the survey package" by Greg Freedman, 2022-02-20. Link to Discussion, Examples and Code

Working Version of R Code for Archer and Lemeshow GOF test, Developed by Yajuan Si and Kevin Pritchard with assistance from Brady West, University of Michigan, July 16 2022. Link to R Code

Weight Calibration across Packages, Presentation by Stas Kolenikov, 9/23/2019. Link to Presentation

R Package pwlmm: PWIGLS for Two-Level Multivariate and Multilevel Linear Models, Author: Alinne Veiga, Published 2022-06-13. Link to R Package

R Package "svrep", Tools for Creating, Updating, and Analyzing Survey Replicate Weights, Author: Benjamin Schneider, February 7, 2023. Link to PDF

Statistical Resources for Analysis of Survey Data

University of Michigan

Institute for Social Research-Summer Institute www.isr.umich.edu/src/si

IVEware (Imputation and Variance Estimation software) iveware.org

ICPSR summer institute https://www.icpsr.umich.edu/icpsrweb/sumprog/

Center for Statistical Consulting and Research www.umich.edu/~cscar/

University of California-Los Angeles

Statistical and Survey Data Analysis https://idre.ucla.edu

University of North Carolina-Chapel Hill

Population Center https://www.cpc.unc.edu/

American Statistical Association

Home Page https://www.amstat.org/

Survey Data Analysis Publications - General Survey Data Analysis Topics (since 2015)

This section is designed to provide information about key updates in publications regarding Survey Data analysis. We will add to the list as new publications emerge.

Mplus Notes area with many articles about survey data analysis: https://statmodel.com/resrchpap.shtml.

Presentation on AIC and BIC for Survey Data by Thomas Lumley and Alastair Scott: Link to Presentation

Lumley and Scott, AIC AND BIC FOR MODELING WITH COMPLEX SURVEY DATA, Journal of Survey Statistics and Methodology,2015, Link to Paper

Thompson, Mary E., Using Longitudinal Complex Survey Data, Annual Review of Statistics and Its Application,2015. 2:305-20, Link to Paper

Bridget L. Ryan, John Koval, Bradley Corbett, Amardeep Thind, M. Karen Campbell, and Moira Stewart, Assessing the impact of potentially influential observations in weighted logistic regression, The Research Data Centres Information and Technical Bulletin, Catalogue no. 12-002‑X No. 2015001, Link to Paper

Jianzhu Li and Richard Valliant, Linear Regression Diagnostics in Cluster Samples,Journal of Official Statistics, Vol. 31, No. 1, 2015, pp. 61-75, Link to Paper

Miles, Andrew, Obtaining Predictions from Models Fit to Multiply Imputed Data, Sociological Methods & Research, pp. 1-11, 2015, Link to Paper

Luchman, J.N., Determining Subgroup Difference Importance with Complex Survey Designs An Application of Weighted Dominance Analysis, Survey Practice, Vol. 8, no 4, 2015, Link to Paper

Oya Kalaycioglu,Andrew Copas, Michael King and Rumana Z. Omar, A comparison of multiple-imputation methods for handling missing data in repeated measurements observational studies, Journal of the Royal Statistical Society, June 2015, Link to Paper

Natalie Dean, Marcello Pagano, EVALUATING CONFIDENCE INTERVAL METHODS FOR BINOMIAL PROPORTIONS IN CLUSTERED SURVEYS, Journal of Survey Statistics and Methodology, October 2015, Link to Paper

Zhou, H., Elliott, M.R., Raghunathan, T.E. (2015). "Synthetic Multiple Imputation Procedure For Multi-Stage Complex Samples," to appear in Journal of Official Statistics soon.

Zhou, H., Elliott, M.R., Raghunathan, T.E. (2015). "A Two-Step Semiparametric Method to Accommodate Sampling Weights in Multiple Imputation," in Biometrics 2015 Sep 22. Link to Paper

Zhou, H., Elliott, M.R., Raghunathan, T.E. (2015). "Multiple Imputation In Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap," to appear in Journal of Survey Statistics and Methodology soon.

Stapleton, L. and Kang, Y. (2016). "Design Effects of Multilevel Estimates From National Probability Samples", Sociological Methods & Research 0049124116630563, first published on February 11, 2016 as doi:10.1177/0049124116630563, Link to Paper

Daoying Lin, Lingxiao Wang, and Yan Li, "HAPLOTYPE-BASED STATISTICAL INFERENCE FOR POPULATION-BASED CASE-CONTROL AND CROSS-SECTIONAL STUDIES WITH COMPLEX SAMPLE DESIGNS", J Surv Stat Methodol published 25 April 2016, 10.1093/jssam/smv040. Link to Paper

Bollen,K., Biemer,P., Karr,A., Tueller,S., Berzofsky,M.,"Are Survey Weights Needed? A Review of Diagnostic Tests in Regression Analysis", Annual Review of Statistics and Its Application Vol. 3: 375-392 (Volume publication date June 2016). Link to Paper

Hanzhi Zhou, Michael R. Elliott, and Trivellore E. Raghunathan,"Multiple Imputation in Two-stage Cluster Samples Using the Weighted Finite Population Bayesian Bootstrap", J Surv Stat Methodol 2016 4: 139-170. Link to Paper

Minsun Kim Riddles, Jae Kwang Kim, and Jongho Im, "A Propensity-score-adjustment Method for Nonignorable Nonresponse", J Surv Stat Methodol 2016 4: 215-245. . Link to Paper

Brady T. West, Joseph W. Sakshaug, Guy Alain S. Aurelien, "How Big of a Problem is Analytic Error in Secondary Analyses of Survey Data?", Published: June 29,https://dx.doi.org/10.1371/journal.pone.0158120. Link to Paper

Ismael Flores Cervantes and J. Michael Brick, "Nonresponse adjustments with misspecified models in stratified designs", Survey Methodology, Catalogue no. 12-001-X, Release date: June 22, 2016. Link to Paper

Xiaying Zheng and Ji Seung Yang, "Using Sample Weights in Item Response Data Analysis Under Complex Sample Designs", L.A. van der Ark et al. (eds.), Quantitative Psychology Research, Springer, Proceedings in Mathematics & Statistics 167, DOI 10.1007/978-3-319-38759-8_10. Link to Paper

Xing Lui, "Fitting Proportional Odds Models for Complex Sample Survey Data with SAS, IBM SPSS, Stata, and R", General Linear Model Journal, 2016, Vol. 42(2). Link to Paper

Toth, Daniel, Bureau of Labor Statistics, "An R Package for Modeling Survey Data with Regression Trees", WSS Seminar, 2017. Link to Presentation

Hsu HY1, Lin JJH2, Skidmore ST3, "Analyzing individual growth with clustered longitudinal data: A comparison between model-based and design-based multilevel approaches", Behav Res Methods. 2017 Jun 20. doi: 10.3758/s13428-017-0905-7. [Epub ahead of print]. Link to Paper

Qixuan Chen, Michael R. Elliott, David Haziza, Ye Yang, Malay Ghosh, Roderick J. A. Little, Joseph Sedransk, and Mary Thompson, "Approaches to Improving Survey-Weighted Estimates", Statist. Sci.Volume 32, Number 2 (2017), 227-248. Link to Paper

Kott, Phillip S. A design-sensitive approach to fitting regression models with complex survey data. Statist. Surv. 12 (2018), 1--17. doi:10.1214/17-SS118. Link to Paper

von Hippel, Paul T. How Many Imputations Do You Need? A Twostage Calculation Using a Quadratic Rule. Sociological Methods & Research, Article first published online: January 18, 2018. Link to Paper

Brady T. West PhD, Linda Beer PhD, Garrett W. Gremel BS, John Weiser MD, MPH, Christopher H. Johnson MS, Shikha Garg MD, MPH, and Jacek Skarbinski MD., "Weighted Multilevel Models: A Case Study", American Journal of Public Health (AJPH), Article first published online: October 9, 2015. Link to Paper

Ashley L. Buchanan, Michael G. Hudgens, Stephen R. Cole, Katie R. Mollan, Paul E. Sax, Eric S. Daar, Adaora A. Adimora, Joseph J. Eron and Michael J. Mugavero, "Generalizing evidence from randomized trials using inverse probability of sampling weights", Version of Record online: 26 FEB 2018 | DOI: 10.1111/rssa.12357. Link to Paper

Lumley, Thomas, Description and Link to R package for mixed models under complex sampling. Link to Paper

J.N.K. Rao, Francois Verret and Mike A. Hidiroglou. "A weighted composite likelihood approach to inference for two-level models from survey data", Survey Methodology, December 2013, 263 Vol. 39, No. 2, pp. 263-282. Statistics Canada, Catalogue No. 12-001-X. Link to Paper

Daniel Zhao and Sixia Chen, "Quantile Regression Analysis of Survey Data Under Informative Sampling", JSM 2018 Online Program. . Link to Paper Abstract Link to Code

Giovanni Nattino and Bo Lu, "Estimating Causal Effects with Propensity Score in Cluster Sample Surveys", JSM 2018 Online Program. . Link to Paper Abstract

Sixia Chen and Yan Daniel Zhao, "Quantile Regression Analysis of Survey Data Under Informative Sampling", Journal of Survey Statistics and Methodology, Published: 29 October 2018. . Link to Paper Abstract

Carolina Franco, Rodericak J A Little, Thomas A Louis, Eric V Slud, "Comparative Study of Confidence Intervals for Proportions in Complex Sample Surveys", Journal of Survey Statistics and Methodology, smy019, Published: 07 January 2019. Link to Paper

Xu Qin, Guanglei Hong, Jonah Deutsch, and Edward Bein, "Multisite causal mediation analysis in the presence of complex sample and survey designs and non-random non-response", Journal of the Royal Statistics Society, First published: 14 April 2019. Link to Paper

Natalie A. Koziol,"Weighted Multilevel Versus Robust Single-Level Methods for Analyzing Subpopulation Data", Methodology (2019),15,pp. 67-76, 2019 Hogrefe Publishing. Link to Paper

Carolina Franco, Roderick J A Little, Thomas A Louis, Eric V Slud, "Comparative Study of Confidence Intervals for Proportions in Complex Sample Surveys", Journal of Survey Statistics and Methodology, Volume 7, Issue 3, September 2019, Pages 334–364. Link to Paper

Toth, Daniell, "A Permutation Test on Complex Sample Data", Journal of Survey Statistics and Methodology, smz018, Published:13 August 2019. Link to Paper

Jacques Muthusi, Samuel Mwalili, Peter Young, "%svy_logistic_regression: A generic SAS macro for simple and multiple logistic regression and creating quality publication-ready tables using survey or non-survey data", Plos One, Published: September 3, 2019. Link to Paper

M Quartagno, J R Carpenter, H Goldstein, "Multiple Imputation with Survey Weights: A Multilevel Approach", Journal of Survey Statistics and Methodology, smz036, https://doi.org/10.1093/jssam/smz036, Published: 13 September 2019. Link to Paper

Jihnhee Yu, Ziqiang Chen, Kan Wang and Mine Tezal, "Suggestion of confidence interval methods for the Cronbach alpha in application to complex survey data", Statistics Canada,Survey Methodology Journal, https://www150.statcan.gc.ca/n1/pub/12-001-x/12-001-x2019003-eng.htm. Link to Paper

Gosta Andersson, "Optimal" calibration weights under unit nonresponse in survey sampling, Statistics Canada,Survey Methodology Journal, https://www150.statcan.gc.ca/n1/pub/12-001-x/12-001-x2019003-eng.htm. Link to Paper

Jing Wang, "The Pseudo Maximum Likelihood Estimator for Quantiles of Survey Variables", Journal of Statistics and Methodolgy, https://academic.oup.com/jssam, December 17, 2019. Link to Paper

Paul T. von Hippel, "How Many Imputations Do You Need? A Two-stage Calculation Using a Quadratic Rule", First Published January 18, 2018 Research Article. Link to Paper

Phillip S. Kott, "Calibration-weighting a stratified simple random sample with SUDAAN" RTI Press, March 2022, DOI: 10.3768/rtipress.2022.mr.0048.2204. Link to Paper

Kott, P. S. (2022). The Role of Weights in Regression Modeling and Imputation. RTI Press Publication No. MR-0047-2203. Research Triangle Park, NC: RTI Press. https://doi.org/10.3768/rtipress.2022.mr.0047.2203. Link to Paper

Sixia Chen, Keith Rust Author, "An Extension of Kish's Formula for Design Effects to Two- and Three-Stage Designs With Stratification", Journal of Survey Statistics and Methodology, Volume 5, Issue 2, June 2017. Link to Paper

Pedro Luis do N. Silva,Fernando Antonio da S. Moura, Fitting multivariate multilevel models under informative sampling, Journal of the Royal Statistical Society: Series A (Statistics in Society), First published: 25 August 2022. Link to Paper

Danny Pfeffermann, "Time series modelling of repeated survey data for estimation of finite population parameters", Journal of the Royal Statistical Society: Series A (Statistics in Society), First published: 11 October 2022. Link to Paper

Robert G. Clark,David G. Steel, "Sample design for analysis using high-influence probability sampling", Journal of the Royal Statistical Society: Series A (Statistics in Society),First published: 23 October 2022. Link to Paper

Wayne A. Fuller, "Post-strata based on sample quantiles", Journal of the Royal Statistical Society: Series A (Statistics in Society), 2022, First published: 22 February 2022. Link to Paper

Jae Kwang Kim, J.N.K. Rao, Yonghyun Kwon, "Analysis of clustered survey data based on two-stage informative sampling and associated two-level models", Journal of the Royal Statistical Society: Series A (Statistics in Society), First published: 30 March 2022. Link to Paper

Pedro Luis do N. Silva, Fernando Antônio da S. Moura, "Fitting multivariate multilevel models under informative sampling", Journal of the Royal Statistical Society: Series A (Statistics in Society), First published: 25 August 2022. Link to Paper

Nathaniel MacNell, Lydia Feinstein, Jesse Wilkerson, Paivi M. Salo, Samantha A. Molsberry, Michael B. Fessler, Peter S. Thorne, Alison A. Motsinger-Reif, Darryl C. Zeldin, "Implementing machine learning methods with complex survey data: Lessons learned on the impacts of accounting sampling weights in gradient boosting", Plos One, Published: January 13, 2023. Link to Paper

Jae-kwang Kim, J. N. K. Rao and Zhonglei Wang, "Hypotheses Testing from Complex Survey Data Using Bootstrap Weights: A Unified Approach", Journal of the American Statistical Association, Published 02 Mar 2023. Link to Paper

Jianwen Cai, Donglin Zeng, Haolin Li, Nicole M. Butera, Pedro L. Baldoni, Poulami Maitra, Li Dong, "Comparisons of statistical methods for handling attrition in a follow-up visit with complex survey sampling", Statistics in Medicine, First published: 07 March 2023. Link to Paper

Jean Opsomer (with Minsun Riddles) Westat, "Fitting Classification Trees to Complex Survey Data", Presentation Slides from IASS, May 31, 2023. Link to Presentation

Amaia Iparragirre, Thomas Lumley, Irantzu Barrio1, and Inmaculada Arostegui, "Variable selection with LASSO regression for complex survey data", Stat, First published: 19 April 2023. Link to Paper

Jiurui Tang, D Sunshine Hillygus, Jerome P Reiter, "Using Auxiliary Marginal Distributions in Imputations for Nonresponse while Accounting for Survey Weights, with Application to Estimating Voter Turnout", Journal of Survey Statistics and Methodology, Published: 17 August 2023. Link to Paper

Steven G. Heeringa PhD, Patricia A. Berglund MBA, Brady T. West PhD, Edmundo R. Mellipilan MS, Kenneth Portier PhD, "Attributable fraction estimation from complex sample survey data", Annals of Epidemiology Volume 25, Issue 3, March 2015, Pages 174-178. Link to Paper with R code Link to Bootstrap SAS Code Link to JRR SAS Code

Djalma Pessoa [aut], Anthony Damico [aut, cre], Guilherme Jacob [aut], "R convey: Income Concentration Analysis with Complex Survey Samples", January 2024. Link to R Convey Package Link to textbook and introductory flowchart

Survey Data Analysis Publications - Bayes Related (since 2015)

Si, Y., Pillai, N.S., and Gelman, A., "Bayesian nonparametric weighted sampling inference" Bayesian Analysis, 2015, 10(3) 605-625. Link to Paper Link to STAN Codes for Binary Outcome Link to STAN Codes for Continuous Outcome

Goldstein, Harvey; Carpenter, James; Kenward, Michael. "Bayesian models for weighted data with missing values: a bootstrap approach." In: Journal of the Royal Statistical Society: Series C, 18.01.2018. Link to Paper

Terrance D. Savitsky, Matthew R. Williams. "Bayesian Mixed Effects Model Estimation under Informative Sampling". arXiv:1904.07680 [stat.ME] (Submitted on 16 Apr 2019). Link to Paper

Terrance D. Savitsky, Matthew R. Williams. "Bayesian Uncertainty Estimation Under Complex Sampling". arXiv.org/abs/1807.11796v1 [stat.ME], Submitted on 31JUL2018. Link to Paper

Luis G. Leon-Novelo and Terrance D. Savitsky, "Fully Bayesian estimation under informative sampling". Electronic Journal of Statistics Volume 13, Number 1 (2019), 1608-1645. Link to Paper

Matthew R. Williams and Terrance D. Savitsky, "Bayesian Estimation Under Informative Sampling with Unattenuated Dependence", Bayesian Analysis, 2018. Link to Paper

Yutao Liu, Qixuan Chen, "Bayesian Inference of Finite Population Quantiles for Skewed Survey Data Using Skew-Normal Penalized Spline Regression", Journal of Survey Statistics and Methodology, Published: 3 September 2019. Link to Paper

Matthew R. Williams and Terrance D. Savitsky, "Uncertainty Estimation for Pseudo-Bayesian Inference Under Complex Sampling", International Statistics Review, First published:08 June 2020. Link to Paper

R Hornby, MR Williams, TD Savitsky, M Elkasabi, "csSampling: An R Package for Bayesian Models for Complex Survey Data", arXiv preprint arXiv:2308.06845, 2023. Link to Package

Errata Second Edition

Please check this link for corrections to ASDA Second Edition: ASDA Second Edition Errata

Errata First Edition

Please check this link for corrections to ASDA First Edition : ASDA Errata