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Assessing the accuracy of response propensities in longitudinal studies
Survey Methodology, 2010The omnipresence of non-response in longitudinal studies is addressed by assessing the accuracy ofstatistical models constructed to predict different types of non-response. Particular attention is paid tosummary measures derived from receiver operating characteristic curves and logit rank plots as ways ofassessing accuracy.
Plewis, Ian +2 more
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Correcting for Survey Nonresponse Using Variable Response Propensity
Journal of the American Statistical Association, 2010All surveys with less than full response potentially suffer from nonresponse bias. Poststratification weights can only correct for selection into the sample based on observables whose distribution is known in the population. Variables such as gender, race, income, and region satisfy this requirement because they are available from the U.S.
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Testing Homogeneity of Response Propensities in Surveys
2022Juan Luis Moreno-Rebollo +2 more
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Does the choice of link function matter in response propensity modelling?
Model Assisted Statistics and Applications, 2006Response propensity models are currently often used in survey research when predicting the response behaviour and then adjusting for biases due to non-response. Such a model yields the propensity scores or the predicted response probabilities both for the respondents and non-respondents.
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A Bayesian approach with propensity scores for prediction of unknown responses
Journal of the Korean Data And Information Science Society, 2021Juhee Lee, Eun Jin Jang, Dal Ho Kim
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In Response: Using Propensity Score Matching to Balance the Baseline Characteristics
Journal of Thoracic Oncology, 2021openaire +2 more sources
Endogenous treatment effect for any response conditional on control propensity score
Statistics and Probability Letters, 2023Jin-Young Choi +2 more
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