Albert, J. H., and Chib, S.
1993. Bayesian analysis of binary and polychotomous response data. Journal of the American Statistical Association
2000. Multiple imputation for missing data: A cautionary tale. Sociological Methods and Research
Bartels, L. M.
1999. Panel effects in the American National Election Studies. Political Analysis
Behr, A., Bellgardt, E., and Rendtel, U.
2005. Extent and determinants of panel attrition in the European community household panel. European Sociological Review
2008a. Inference in panel data models under attrition caused by unobservables. Journal of Econometrics
2008b. Inference in panel data models under attrition caused by unobservables. Journal of Econometrics
1993. The phantom respondents: Opinion surveys and political representation. Ann Arbor: University of Michigan Press.
Brown, C. H.
1990. Protecting against nonrandomly missing data in longitudinal studies. Biometrics
Burgette, L. F., and Reiter, J. P.
2010. Multiple imputation via sequential regression trees. American Journal of Epidemiology
Callegaro, M., and DiSogra, C.
2008. Computing response metrics for online panels. Public Opinion Quarterly
2001. Panel bias from attrition and conditioning: A case study of the Knowledge Networks panel. In AAPOR 55th Annual Conference.
Cranmer, S. J., and Gill, J.
2013. We have to be discrete about this: A non-parametric imputation technique for missing categorical data. British Journal of Political Science
Deng, Y., Hillygus, D. S., Reiter, J. P., Si, Y., and Zheng, S.
2013. Handling attrition in longitudinal studies: The case for refreshment samples. Statistical Science
Diggle, P., and Kenward, M. G.
1994. Informative dropout in longitudinal data analysis. Journal of the Royal Statistical Society Series C (Applied Statistics)
Dunson, D. B., and Xing, C.
2009. Nonparametric Bayes modeling of multivariate categorical data. Journal of the American Statistical Association
Erosheva, E. A., Fienberg, S. E., and Junker, B. W.
2002. Alternative statistical models and representations for large sparse multi-dimensional contingency tables. Annales de la Faculté des Sciences de Toulouse
Frankel, L., and Hillygus, S.
2013. Looking beyond demographics: Panel attrition in the ANES and GSS. Political Analysis
Frick, J. R., Goebel, J., Schechtman, E., Wagner, G. G., and Yitzhaki, S.
2006. Using analysis of Gini (ANOGI) for detecting whether two subsamples represent the same universe: The German Socio-Economic Panel Study (SOEP) experience. Sociological Methods Research
Gelman, A., Van Mechelen, I., Verbeke, G., Heitjan, D. F., and Meulders, M.
2005. Multiple imputation for model checking: Completed-data plots with missing and latent data. Biometrics
2010. A Bayesian hierarchical topic model for political texts: Measuring expresses agendas in Senate press releases. Political Analysis
Hausman, J. A., and Wise, D. A.
1979. Attrition bias in experimental and panel data: The Gary income maintenance experiment. Econometrica
He, Y., Zaslavsky, A. M., and Landrum, M. B.
2010. Multiple imputation in a large-scale complex survey: A guide. Statistical Methods in Medical Research
1997. Russia longitudinal monitoring survey sample attrition, replenishment, and weighting: Rounds V-VII. University of Michigan Institute for Social Research.
Henderson, M., and Hillygus, D. S.
2011. The dynamics of health care opinion, 2008–2010: Partisanship, self-interest, and racial resentment. Journal of Health Politics, Policy, and Law
Henderson, M., Hillygus, D., and Tompson, T.
2010. “Sour grapes” or rational voting? Voter decision making among thwarted primary voters in 2008. Public Opinion Quarterly
Hirano, K., Imbens, G. W., Ridder, G., and Rubin, D. B.
1998. Combining panel data sets with attrition and refreshment samples. Technical report 230, National Bureau of Economic Research.
Hirano, K., Imbens, G. W., Ridder, G., and Rubin, D. B.
2001. Combining panel data sets with attrition and refreshment samples. Econometrica
Hogan, J. W., and Daniels, M. J.
2008. Missing data in longitudinal studies. Boca Raton, FL: Chapman and Hall.
Holmes, C. C., and Held, L.
2006. Bayesian auxiliary variable models for binary and multinomial regression. Bayesian Analysis
Honaker, J., and King, G.
2010. What to do about missing values in time-series cross-section data. American Journal of Political Science
Ishwaran, H., and James, L. F.
2001. Gibbs sampling for stick-breaking priors. Journal of the American Statistical Association
Iyengar, S., Sood, G., and Lelkes, Y.
2012. Affect, not ideology: A social identity perspective on polarization. Public Opinion Quarterly
Keeter, S., Kennedy, C., Dimock, M., Best, J., and Craighill, P.
2006. Gauging the impact of growing nonresponse on estimates from a national RDD telephone survey. Public Opinion Quarterly
Kenward, M. G.
1998. Selection models for repeated measurements with non-random dropout: An illustration of sensitivity. Statistics in Medicine
Kenward, M. G., Molenberghs, G., and Thijs, H.
2003. Pattern-mixture models with proper time dependence. Biometrika
King, G., Honaker, J., Joseph, A., and Scheve, K.
2001. Analyzing incomplete political science data: An alternative algorithm for multiple imputation. American Political Science Review
Kish, L., and Hess, I.
1959. A “replacement” procedure for reducing the bias of nonresponse. American Statistician
Kropko, J., Goodrich, B., Gelman, A., and Hill, J.
2014. Multiple imputation for continuous and categorical data: Comparing joint multivariate normal and conditional approaches. Political Analysis. Published online doi:10.1093/pan/mpu007.
Kruse, Y., Callegaro, M., Dennis, J., Subias, S., Lawrence, M., DiSogra, C., and Tompson, T.
2009. Panel conditioning and attrition in the AP-Yahoo! News Election Panel Study. In 64th Conference of the American Association for Public Opinion Research (AAPOR). Hollywood, FL.
Kyung, M., Gill, J., and Casella, G.
2011. New findings from terrorism data: Dirichlet process random effects models for latent groups. Journal of the Royal Statistical Society Series C (Applied Statistics)
Lin, I., and Schaeffer, N. C.
1995. Using survey participants to estimate the impact of nonparticipation. Public Opinion Quarterly
Little, R. J. A.
1993. Pattern-mixture models for multivariate incomplete data. Journal of the American Statistical Association
Little, R. J. A., and Rubin, D. B.
2002. Statistical Analysis with Missing Data. 2nd ed. New York: John Wiley & Sons.
Little, R. J. A., and Wang, Y.
1996. Pattern-mixture models for multivariate incomplete data with covariates. Biometrics
1994. Posterior predictive p-values. Annals of Statistics
Olsen, R. J.
2005. The problem of respondent attrition: Survey methodology is key. Monthly Labor Review
Olson, K., and Witt, L.
2011. Are we keeping the people who used to stay? Changes in correlates of panel survey attrition over time. Social Science Research
2008. A note on posterior sampling from Dirichlet mixture models. Technical report, Centre for Research in Statistical Methodology, University of Warwick.
Pasek, J., Tahk, A., Lelkes, Y., Krosnick, J. A., Payne, B. K., Akhtar, O., and Tompson, T.
2009. Determinants of turnout and candidate choice in the 2008 US presidential election illuminating the impact of racial prejudice and other considerations. Public Opinion Quarterly
2010. You've either got it or you don't? The stability of political interest over the life cycle. Journal of Politics
Reiter, J. P., Raghunathan, T. E., and Kinney, S.
2006. The importance of modeling the sampling design in multiple imputation for missing data. Survey Methodology
1992. An empirical evaluation of some models for non-random attrition in panel data. Structural Change and Economic Dynamics
Rubin, D. B.
1987. Multiple imputation for nonresponse in surveys. New York: John Wiley & Sons.
Scharfstein, D. O., Rotnitzky, A., and Robins, J. M.
1999. Adjusting for nonignorable dropout using semiparametric nonresponse models. Journal of the American Statistical Association
Schluchte, M. D.
1982. Methods for the analysis of informatively censored longitudinal data. Statistics in Medicine
1994. A constructive definition of Dirichlet priors. Statistica Sinica
Si, Y., and Reiter, J. P.
2013. Nonparametric Bayesian multiple imputation for incomplete categorical variables in large-scale assessment surveys. Journal of Educational and Behavioral Statistics
Si, Y., Reiter, J. P., and Hillygus, D. S.
2014. Replication data for: Semi-parametric selection models for potentially nonignorable attrition in panel studies with refreshment samples. http://dx.doi.org/10.7910/DVN/25367 (accessed April 19, 2014). IQSS Dataverse Network, V1.
Su, Y.-S., Yajima, M., Gelman, A. E., and Hill, J.
2011. Multiple imputation with diagnostics (mi) in R: Opening windows into the black box. Journal of Statistical Software
Thompson, M., Fong, G., Hammond, D., Boudreau, C., Driezen, P., Hyland, A., Borland, R., Cummings, K., Hastings, G., Siahpush, M.
2006. Methods of the International Tobacco Control (ITC) four-country survey. Tobacco Control 15(Suppl. 3) iii12-iii18.
Traugott, M. W., and Tucker, C.
1984. Strategies for predicting whether a citizen will vote and estimation of electoral outcomes. Public Opinion Quarterly
1999. Field substitution and unit nonresponse. Journal of Official Statistics
Vermunt, J. K., Van Ginkel, J. R., Der Ark, V., Andries, L., and Sijtsma, K.
2008. Multiple imputation of incomplete categorical data using latent class analysis. Sociological Methodology
Walker, S. G.
2007. Sampling the Dirichlet mixture models with slices. Computations in Statistics-Simulation and Computation
2002. Estimating dynamic panel data models in political science. Political Analysis
Wissen, L., and Meurs, H.
1989. The Dutch mobility panel: Experiences and evaluation. Transportation
1998. An analysis of attrition in the Panel Study of Income Dynamics and the Survey of Income and Program Participation with an application to a model of labor market behavior. Journal of Human Resources