Does more balanced survey response imply less non-response bias?
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- Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003.
"Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score,"
Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
- Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," NBER Technical Working Papers 0251, National Bureau of Economic Research, Inc.
- Guido Imbens, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometric Society World Congress 2000 Contributed Papers 1166, Econometric Society.
- Heejung Bang & James M. Robins, 2005. "Doubly Robust Estimation in Missing Data and Causal Inference Models," Biometrics, The International Biometric Society, vol. 61(4), pages 962-973, December.
- Shlomo, Natalie & Skinner, Chris J. & Schouten, Barry, 2012. "Estimation of an indicator of the representativeness of survey response," LSE Research Online Documents on Economics 39124, London School of Economics and Political Science, LSE Library.
- Schouten, Barry & Shlomo, Natalie & Skinner, Chris J., 2011. "Indicators for monitoring and improving representativeness of response," LSE Research Online Documents on Economics 39121, London School of Economics and Political Science, LSE Library.
- Robert M. Groves & Steven G. Heeringa, 2006. "Responsive design for household surveys: tools for actively controlling survey errors and costs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 439-457, July.
- Annemieke Luiten & Barry Schouten, 2013. "Tailored fieldwork design to increase representative household survey response: an experiment in the Survey of Consumer Satisfaction," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(1), pages 169-189, January.
- repec:mpr:mprres:4780 is not listed on IDEAS
- J. Michael Brick & Michael E. Jones, 2008. "Propensity to respond and nonresponse bias," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 51-73.
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- Tobias Gummer & Pablo Christmann & Sascha Verhoeven & Christof Wolf, 2022. "Using a responsive survey design to innovate self‐administered mixed‐mode surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 916-932, July.
- Särndal Carl-Erik & Lundquist Peter, 2017. "Inconsistent Regression and Nonresponse Bias: Exploring Their Relationship as a Function of Response Imbalance," Journal of Official Statistics, Sciendo, vol. 33(3), pages 709-734, September.
- Brick J. Michael & Tourangeau Roger, 2017. "Responsive Survey Designs for Reducing Nonresponse Bias," Journal of Official Statistics, Sciendo, vol. 33(3), pages 735-752, September.
- Wagner James & Olson Kristen, 2018. "An Analysis of Interviewer Travel and Field Outcomes in Two Field Surveys," Journal of Official Statistics, Sciendo, vol. 34(1), pages 211-237, March.
- Särndal Carl-Erik & Traat Imbi & Lumiste Kaur, 2018. "Interaction Between Data Collection And Estimation Phases In Surveys With Nonresponse," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 183-200, June.
- Jamie C. Moore & Peter W. F. Smith & Gabriele B. Durrant, 2018. "Correlates of record linkage and estimating risks of non‐linkage biases in business data sets," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1211-1230, October.
- Carl-Erik Särndal & Imbi Traat & Kaur Lumiste, 2018. "Interaction Between Data Collection And Estimation Phases In Surveys With Nonresponse," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 183-200, June.
- Felderer Barbara & Kirchner Antje & Kreuter Frauke, 2019. "The Effect of Survey Mode on Data Quality: Disentangling Nonresponse and Measurement Error Bias," Journal of Official Statistics, Sciendo, vol. 35(1), pages 93-115, March.
- Roberts Caroline & Herzing Jessica M.E. & Vandenplas Caroline, 2020. "A Validation of R-Indicators as a Measure of the Risk of Bias using Data from a Nonresponse Follow-Up Survey," Journal of Official Statistics, Sciendo, vol. 36(3), pages 675-701, September.
- McCarthy Jaki & Wagner James & Sanders Herschel Lisette, 2017. "The Impact of Targeted Data Collection on Nonresponse Bias in an Establishment Survey: A Simulation Study of Adaptive Survey Design," Journal of Official Statistics, Sciendo, vol. 33(3), pages 857-871, September.
- Jamie C. Moore & Gabriele B. Durrant & Peter W. F. Smith, 2021. "Do coefficients of variation of response propensities approximate non‐response biases during survey data collection?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 301-323, January.
- Burger Joep & Perryck Koen & Schouten Barry, 2017. "Robustness of Adaptive Survey Designs to Inaccuracy of Design Parameters," Journal of Official Statistics, Sciendo, vol. 33(3), pages 687-708, September.
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