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  • Refereed essays Web of Science

    Multiple Imputation of Ordinal Missing Not at Random Data

    We introduce a selection model-based imputation approach to be used within the Fully Conditional Specification (FCS) framework for the Multiple Imputation (MI) of incomplete ordinal variables that are supposed to be Missing Not at Random (MNAR). Thereby, we generalise previous work on this topic which involved binary single-level and multilevel data to ordinal variables. We apply an ordered probit ...

    In: AStA Advances in Statistical Analysis 107 (2023), S. 671–692 | Angelina Hammon
  • Refereed essays Web of Science

    Multiple Imputation of Binary Multilevel Missing Not at Random Data

    We introduce a selection model‐based multilevel imputation approach to be used within the fully conditional specification framework for multiple imputation. Concretely, we apply a censored bivariate probit model to describe binary variables assumed to be missing not at random. The first equation of the model defines the regression model for the missing data mechanism. The second equation specifies ...

    In: Journal of the Royal Statistical Society / Series C 69 (2020), 3, S. 547–564 | Angelina Hammon, Sabine Zinn
  • Other refereed essays

    Attrition and Selectivity of the NEPS Starting Cohorts: An Overview of the Past 8 Years

    This article documents the number of target persons participating in the panel surveys of the National Educational Panel Study (NEPS) as well as the number of respondents who temporarily dropout and of those leaving the panel (attrition). NEPS comprises panel surveys with six mutually exclusive starting cohorts covering the complete life span. Sample sizes, numbers of participants and temporary as ...

    In: AStA Wirtschafts- und Sozialstatistisches Archiv (2020), 14, S. 163–206 | Sabine Zinn, Ariane Würbach, Hans Walter Steinhauer, Angelina Hammon
3 results, from 1
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