Journal ArticleDOI
Inference and missing data
TLDR
In this article, it was shown that ignoring the process that causes missing data when making sampling distribution inferences about the parameter of the data, θ, is generally appropriate if and only if the missing data are missing at random and the observed data are observed at random, and then such inferences are generally conditional on the observed pattern of missing data.Abstract:
Two results are presented concerning inference when data may be missing. First, ignoring the process that causes missing data when making sampling distribution inferences about the parameter of the data, θ, is generally appropriate if and only if the missing data are “missing at random” and the observed data are “observed at random,” and then such inferences are generally conditional on the observed pattern of missing data. Second, ignoring the process that causes missing data when making Bayesian inferences about θ is generally appropriate if and only if the missing data are missing at random and the parameter of the missing data is “independent” of θ. Examples and discussion indicating the implications of these results are included.read more
Citations
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Journal ArticleDOI
Missing data methods for arbitrary missingness with small samples
TL;DR: A simulation study to compare and assess the small sample performance of maximum likelihood, listwise deletion, joint multiple imputation, and fully conditional specification multiple imputations for a single-level regression model with a continuous outcome showed that, provided assumptions are met, jointmultiple imputation unanimously performed best of the methods examined in the conditions under study.
Journal ArticleDOI
GSTM1, GSTT1, and GSTP1 polymorphisms and associations between air pollutants and markers of insulin resistance in elderly Koreans.
Jin Hee Kim,Yun-Chul Hong +1 more
TL;DR: The results suggest that PM10, O3, and NO2 may increase IR in the elderly, and that GSTM1- null, GSTT1-null, and GSTP1 AG or GG genotypes may increase susceptibility to potential effects of ambient air pollutants on IR.
Journal ArticleDOI
A Heckman Selection-t Model
TL;DR: In this article, a new link between sample selection models and extended skew-elliptical distributions is established, which allows the selection-t (SLt) model, which models the error distribution using a St...
Journal ArticleDOI
Efficacy of daily intake of Lactobacillus casei Shirota on respiratory symptoms and influenza vaccination immune response: a randomized, double-blind, placebo-controlled trial in healthy elderly nursing home residents
Karolien Van Puyenbroeck,Niel Hens,Samuel Coenen,Barbara Michiels,Caroline Beunckens,Geert Molenberghs,Paul Van Royen,Veronique Verhoeven +7 more
TL;DR: The results of this study show that daily consumption of a fermented milk drink that contains LcS has no statistically or clinically significant effect on the protection against respiratory symptoms.
Journal ArticleDOI
Marketing and Organisational Innovations in Entrepreneurial Innovation Processes and their Relation to Market Structure and Firm Characteristics
Torben Schubert,Torben Schubert +1 more
TL;DR: In this article, the influence of marketing and organisational changes on the innovation process is analyzed using data from the German community innovation survey 2007, and it is shown that firms choose broad innovation strategies, which combine marketing and process innovations, if they have large internal resources and intermediate market power.
References
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Book
Bayesian inference in statistical analysis
George E. P. Box,George C. Tiao +1 more
TL;DR: In this article, the effect of non-normality on inference about a population mean with generalizations was investigated. But the authors focused on the effect on the mean with information from more than one source.
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Bayesian Inference in Statistical Analysis
Journal ArticleDOI
Maximum Likelihood Estimates for a Multivariate Normal Distribution when Some Observations are Missing
TL;DR: In this paper, the authors give an approach to derive maximum likelihood estimates of parameters of multivariate normal distributions in cases where some observations are missing (Edgett [2] and Lord [3], [4]).
Journal ArticleDOI
Missing Observations in Multivariate Statistics I. Review of the Literature
TL;DR: In this paper, a review of the literature on the problem of handling multivariate data with observations missing on some or all of the variables under study is presented, where the authors examine the ways that statisticians have devised to estimate means, variances, correlations and linear regression functions.