Missing data: Our view of the state of the art.
Joseph L. Schafer,John W. Graham +1 more
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TLDR
2 general approaches that come highly recommended: maximum likelihood (ML) and Bayesian multiple imputation (MI) are presented and may eventually extend the ML and MI methods that currently represent the state of the art.Abstract:
Statistical procedures for missing data have vastly improved, yet misconception and unsound practice still abound. The authors frame the missing-data problem, review methods, offer advice, and raise issues that remain unresolved. They clear up common misunderstandings regarding the missing at random (MAR) concept. They summarize the evidence against older procedures and, with few exceptions, discourage their use. They present, in both technical and practical language, 2 general approaches that come highly recommended: maximum likelihood (ML) and Bayesian multiple imputation (MI). Newer developments are discussed, including some for dealing with missing data that are not MAR. Although not yet in the mainstream, these procedures may eventually extend the ML and MI methods that currently represent the state of the art.read more
Citations
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Stable Early Maternal Report of Behavioral Inhibition Predicts Lifetime Social Anxiety Disorder in Adolescence
Andrea Chronis-Tuscano,Kathryn A. Degnan,Daniel S. Pine,Koraly Pérez-Edgar,Heather A. Henderson,Yamalis Diaz,Veronica L. Raggi,Nathan A. Fox +7 more
TL;DR: Findings suggesting that stable maternal-reported early BI predicts lifetime SAD have important implications for the early identification and prevention of SAD.
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Analysis of Longitudinal Data: The Integration of Theoretical Model, Temporal Design, and Statistical Model
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Handling Item-Level Missing Data Simpler Is Just as Good
TL;DR: In this article, the authors assess whether advanced methods of handling item-level missing data performed equivalently to simpler methods in designs similar to those counseling psychologists typically engage in, and support the use of available case analysis when dealing with low-level itemlevel missingness.
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Bringing Values Back In The Adequacy of the European Social Survey to Measure Values in 20 Countries
TL;DR: The semi-annual Eu- ropean Social Survey (ESS) includes a new 21-item instrument to measure the importance of the 10 basic values of the Schwartz theory.
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Explaining Radical Group Behavior: Developing Emotion and Efficacy Routes to Normative and Nonnormative Collective Action
Nicole Tausch,Julia C. Becker,Russell Spears,Oliver Christ,Rim Saab,Purnima Singh,Roomana N. Siddiqui +6 more
TL;DR: It is argued that the relations between emotions, efficacy, and action differ for more extreme, nonnormative actions and proposed that contempt, which, unlike anger, entails psychological distancing and a lack of reconciliatory intentions, predicts non normative action.
References
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Journal ArticleDOI
Maximum likelihood from incomplete data via the EM algorithm
Book
Generalized Linear Models
Peter McCullagh,John A. Nelder +1 more
TL;DR: In this paper, a generalization of the analysis of variance is given for these models using log- likelihoods, illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables), and gamma (variance components).
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Statistical Analysis with Missing Data
TL;DR: This work states that maximum Likelihood for General Patterns of Missing Data: Introduction and Theory with Ignorable Nonresponse and large-Sample Inference Based on Maximum Likelihood Estimates is likely to be high.
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Bayesian Data Analysis
TL;DR: Detailed notes on Bayesian Computation Basics of Markov Chain Simulation, Regression Models, and Asymptotic Theorems are provided.
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Multiple imputation for nonresponse in surveys
TL;DR: In this article, a survey of drinking behavior among men of retirement age was conducted and the results showed that the majority of the participants reported that they did not receive any benefits from the Social Security Administration.
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