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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Latino Adolescents’ Ethnic Identity: Is There a Developmental Progression and Does Growth in Ethnic Identity Predict Growth in Self-Esteem?
TL;DR: Findings from multiple-group latent growth curve models revealed that exploration, resolution, and affirmation all increased significantly from middle to late adolescence for Latina girls and for Latino boys, only affirmation increased significantly.
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Relationship of organizational culture, teamwork and job satisfaction in interprofessional teams
TL;DR: The results showed that 35 % of job satisfaction is predicted by a structural equation model that includes both organizational culture and teamwork, and showed that the effect of organizational culture is completely mediated by interprofessional teamwork.
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The state of the art and future opportunities for using longitudinal n-of-1 methods in health behaviour research: a systematic literature overview.
Suzanne McDonald,Francis Quinn,Rute Vieira,Nicola O'Brien,Martin White,Derek Johnston,Falko F. Sniehotta +6 more
TL;DR: An overview of the scope and opportunities for using n-of-1 methods to answer key questions in health behaviour research is identified.
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A Meta-Analysis of Juvenile Justice Risk Assessment Instruments Predictive Validity by Gender
TL;DR: In this paper, a meta-analysis of risk assessment predictive validity with male and female offenders was conducted and the results indicated that predictive validity estimates are equivalent for both genders and that when gender differences are observed in individual studies, they provide evidence for gender biases in juvenile justice decision-making and case processing rather than for the ineffectiveness of risk assessments with female offenders.
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Predicting the risk of Chronic Kidney Disease in Men and Women in England and Wales: prospective derivation and external validation of the QKidney ® Scores
TL;DR: These new algorithms have the potential to identify high risk patients who might benefit from more detailed assessment, closer monitoring or interventions to reduce their risk of chronic Kidney Disease.
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).
Book
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.
Book
Bayesian Data Analysis
TL;DR: Detailed notes on Bayesian Computation Basics of Markov Chain Simulation, Regression Models, and Asymptotic Theorems are provided.
Book
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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