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Assessing the accuracy of response propensities in longitudinal studies

Survey Methodology, 2010
The 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
openaire   +2 more sources

Correcting for Survey Nonresponse Using Variable Response Propensity

Journal of the American Statistical Association, 2010
All 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.
openaire   +2 more sources

Testing Homogeneity of Response Propensities in Surveys

2022
Juan Luis Moreno-Rebollo   +2 more
openaire   +1 more source

Does the choice of link function matter in response propensity modelling?

Model Assisted Statistics and Applications, 2006
Response 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.
openaire   +2 more sources

A Bayesian approach with propensity scores for prediction of unknown responses

Journal of the Korean Data And Information Science Society, 2021
Juhee Lee, Eun Jin Jang, Dal Ho Kim
openaire   +1 more source

Endogenous treatment effect for any response conditional on control propensity score

Statistics and Probability Letters, 2023
Jin-Young Choi   +2 more
exaly  

Use of Response Propensities

2021
Silvia Biffignandi, Jelke Bethlehem
exaly  

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