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Journal ArticleDOI

The use of multiple imputation for the analysis of missing data.

Sandip Sinharay, +2 more
- 01 Dec 2001 - 
- Vol. 6, Iss: 4, pp 317-329
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TLDR
The idea behind MI, the advantages of MI over existing techniques for addressing missing data, how to do MI for real problems, the software available to implement MI, and the results of a simulation study aimed at finding out how assumptions regarding the imputation model affect the parameter estimates provided by MI are discussed.
Abstract
This article provides a comprehensive review of multiple imputation (MI), a technique for analyzing data sets with missing values. Formally, MI is the process of replacing each missing data point with a set of m > 1 plausible values to generate m complete data sets. These complete data sets are then analyzed by standard statistical software, and the results combined, to give parameter estimates and standard errors that take into account the uncertainty due to the missing data values. This article introduces the idea behind MI, discusses the advantages of MI over existing techniques for addressing missing data, describes how to do MI for real problems, reviews the software available to implement MI, and discusses the results of a simulation study aimed at finding out how assumptions regarding the imputation model affect the parameter estimates provided by MI.

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Citations
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Journal ArticleDOI

Prognostic Factors and Survival Outcome in Patients with Chordoma in the United States: A Population-Based Analysis.

TL;DR: Investigation of prognostic factors in overall survival and disease-specific survival of patients with chordoma found that older age, greater tumor size, and distant metastasis were correlated with decreased survival, whereas surgical resection was correlated with increased survival.
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Identifying atypical cortisol patterns in young children: The benefits of group-based trajectory modeling

TL;DR: This work finds three distinct trajectories of cortisol and demonstrates that the members of these trajectories are measurably different in terms of cortisol levels across context and time and in Terms of the relationship between behavioral problems and parenting.
Journal ArticleDOI

Cervical cancer screening programmes and age-specific coverage estimates for 202 countries and territories worldwide: a review and synthetic analysis

TL;DR: Two in three women aged 30–49 years have never been screened for cervical cancer, and expanding the efforts of surveillance systems in both coverage and quality control are major challenges to achieving the WHO elimination target.
Journal ArticleDOI

Why Missing Data Matter in the Longitudinal Study of Adolescent Development: Using the 4-H Study to Understand the Uses of Different Missing Data Methods

TL;DR: The results showed that three missing data techniques, i.e., listwise deletion, direct maximum likelihood (DirML), and multiple imputation (MI), did not yield comparable results for research questions assessing different aspects of development (i.e, change over time or prediction effects).
References
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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.
Book

Analysis of Incomplete Multivariate Data

TL;DR: The Normal Model Methods for Categorical Data Loglinear Models Methods for Mixed Data and Inference by Data Augmentation Methods for Normal Data provide insights into the construction of categorical and mixed data models.