4 results for “Multiple Imputation (MI)”

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Research ArticleOpen accessEvery word in the titleAN EFFECTIVE TECHNIQUE OF MULTIPLE IMPUTATION IN NONPARAMETRIC QUANTILE REGRESSIONYanan Hu, Qianqian Zhu, Maozai TianIn this study, we consider the nonparametric quantile regression model with the covariates Missing at Random (MAR). Multiple imputation is becoming an increasingly popular approach for analyzing missing data, which combined with quantile regression is not well-developed. We propose an effective and accurate two-stage multiple imputation method for the model based on the quantile regression, which consists of initial imputation … …Journal of Mathematics and Statistics, Vol. 10, Issue 1 · 4 Jan 2014 · 6,813 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsApplication of Multiple Imputations to Freight Transportation Survey Data: A Case Study of Commodity Flow SurveyTerdsak Rongviriyapanich, Akachut SuppiyatrakulProblem statement: Freight transportation data was indispensable input to transportation planning. In Thailand, efforts had been put to collect freight movement data by conducting road side survey and commodity flow survey. The results of these surveys did not produce consistent volume of shipment due to limited sampling coverage and non-response. Nevertheless, freight distribution patterns, which were derived from these surveys, … …American Journal of Engineering and Applied Sciences, Vol. 4, Issue 3 · 18 Aug 2011 · 7,477 accessesView PDF Cite

Research ArticleOpen accessIn the abstractGeneral Linear Models in a Missing Outcome Environment of Clinical Trials Incorporating with Splines for Time-Invariant Continuous AdjustmentMinjeong Park, Dejian Lai, Xianglin L. Du et al.Missing data is a common occurrence in longitudinal studies of health care research. Although many studies have shown the potential usefulness of current missing analyses, e.g., (1) Complete Case (CC) analysis; (2) imputation methods such as Last Observation Carried Forward (LOCF), multiple imputations, Expectation-Maximization algorithm approach; and (3) methods using all available data such as linear mixed model and generalized … …Current Research in Biostatistics, Vol. 5, Issue 1 · 18 Aug 2015 · 7,401 accessesView PDF Cite

Research ArticleOpen accessIn the abstractMethods for Computing Missing Item Response in Psychometric Scale ConstructionOhidul Islam SiddiquiTherapeutic potential of a new antidepressant drug is evaluated frequently based on multi-item psychometric scales. The total score of a psychometric scale is calculated based on the responses of multiple-items, in which each item is scored on a likert scale. Missing responses in some of the items are inevitable and hence it is a problem in calculating the total score … …Current Research in Biostatistics, Vol. 5, Issue 1 · 29 May 2015 · 15,648 accessesView PDF Cite