Small-sample degrees of freedom for multi-component significance tests with multiple imputation for missing data

By Jerome P. Reiter. 2007

87 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/e9e4fc9c4494ec59fbf225fd3c8cb005c4309466

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

New Confidence Intervals and Bias Comparisons Show That Maximum Likelihood Can Beat Multiple Imputation in Small Samples (2013, background): “…of missing-data estimators, which have most commonly examined sample sizes down to n=25 (Lipsitz, Parzen, & Zhao, 2002; Wagstaff & Harel, 2011), although two studies went as low as n=10 (Barnard & Rubin, 1999; von Hippel, 2013b) and two didn’t go below n=40 (Demirtas et al., 2008; Reiter, 2007).”
Multiple Imputation of Missing or Faulty Values Under Linear Constraints (2014, background): “Tests of significance for multicomponent null hypotheses are derived by Li, Raghunathan, and Rubin (1991), Meng and Rubin (1992), and Reiter (2007).”
Nonparametric Bayesian Multiple Imputation for Incomplete Categorical Variables in Large-Scale Assessment Surveys (2013, background): “Tests of significance for multicomponent null hypotheses are derived by Li, Raghunathan, and Rubin (1991), Meng and Rubin (1992), and Reiter (2007).”
Multiple imputation as a flexible tool for missing data handling in clinical research. (2017, background): “Small-sample adjustments to the t statistic appear to offer better Type I error control in very small samples (Barnard& Rubin, 1999; Reiter, 2007), but the choice of reference distribution probably makes little difference in most cases (Liu & Enders, 2016).”
Pooling ANOVA Results From Multiply Imputed Datasets (2016, background): “Reiter (2007) proposed a correction formula that adjusts the denominator degrees of freedom v 1 for ﬁnite samples.”