11 results for “Missing at Random”

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Research ArticleOpen accessIn the keywordsOn the Comparison of Methods of Estimating Missing Values in Rectangular Lattice DesignsAbimibola V. Oladugba, Emmanuel O. Ossai, Tobias E. UgahMissing values occur in almost all research which lead to ambiguity in data analysis. It becomes necessary that appropriate consideration is made in order to provide an efficient and valid analysis. Researchers have developed and compared a variety of methods of estimating missing values in experimental designs; however, no research work has derived and compared methods of estimating missing values, … …Journal of Mathematics and Statistics, Vol. 14, Issue 1 · 11 Oct 2018 · 7,044 accessesView PDF Cite

Review ArticleOpen accessIn the keywordsReview of Zero-Inflated Models with Missing DataT. Martin Lukusa, Shen-Ming Lee, Chin-Shang LiThe literature of count regression models covers a large scope of studies and applications that implemented simple and standard models for count response variables by using Poisson regression models, binomial regression models, negative binomial regression models, geometric regression models, or generalized Poisson regression models. These regression models have received considerable attention in various situations. Nevertheless in many fields, the distribution … …Current Research in Biostatistics, Vol. 7, Issue 1 · 31 Oct 2017 · 14,406 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 abstractResearch on the Link Between Economic Development Variables and the Rate of Access to Drinking Water in Rural Senegal Using Machine LearningAnabilaye Moussa Coly, Alioune Ly, Ndolane Diouf et al.After pre-processing a set of data collected from Senegalese state structures, official United Nations (UN), and world bank sites and after replacing missing values by interpolation using the mean between two values, we study the effect of macroeconomic development variables on the rate of access to drinking water in rural Senegal. To do this, we use Machine Learning (ML) techniques … …American Journal of Applied Sciences, Vol. 20, Issue 1 · 20 Dec 2023 · 6,204 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

Research ArticleOpen accessIn the abstractMISSING DATA IMPUTATION USING WEIGHTED OF REGIME SWITCHING MEAN AND REGRESSIONJumlong Vongprasert, Bhusana PremanodeMissing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. The purpose of this work were first to develop the Weighted of Regime Switching Mean and Regression (WRSMRI) for missing data estimation and secondly to compare its efficiency of estimation and statistical power of a … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 3 May 2014 · 6,704 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA MIXTURE DROPOUT MECHANISM IN A LONGITUDINAL STUDY WITH TWO TIME POINTS: A METHADONE STUDYZohreh Toghrayee, Parvin Jalili, Heng Chin Low, Ardavan TaghvaOne of the most important issues that confront statisticians in longitudinal studies is dropouts. A variety of reasons may lead to withdrawal from a study and produce two different missingness mechanisms, namely, missing at random and non-ignorable dropouts. Nevertheless, none of these mechanisms is tenable in most studies. In addition, it may be that not all of dropouts are nonignorable. … …Journal of Mathematics and Statistics, Vol. 10, Issue 3 · 26 Apr 2014 · 6,724 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAN 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 abstractVideo Streaming in Peer-to-Peer Networks Using Network Coding Renders Efficient Video Cassette Recorder OperationsR. Arockia Xavier Annie, K. V. Pradeepthi, P. YogeshProblem statement: Major technological development in recent years has led to the usage of shared streaming solutions by Peer-to-Peer (P2P) Video-on-Demand (VoD) systems in the Internet. Video streaming in P2P network systems has ample amount of loss of video packets due to network disabilities such as congestion, intrusion, connectivity problems, excessive network collisions etc. Adding onto the video streaming problems, … …Journal of Computer Science, Vol. 8, Issue 10 · 24 Aug 2012 · 6,736 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordClassify Breast Cancer Patients using Hybrid Data-Mining TechniquesFaris E. Mohammed, Nadia Smaoui Zghal, Dalinda Ben Aissa, Mostafa Mahmoud El-GayarAccording to the World Health Organization (WHO), breast cancer is a disease that leads to death, especially for women who have neglected or ignored the risk factors. Doctors can classify patients according to clinical information, famous disease symptoms, or similar cases. But, some cases are difficult to detect early or diagnose accurately. Therefore, the most important challenge faced by researchers … …Journal of Computer Science, Vol. 18, Issue 4 · 12 May 2022 · 6,526 accessesView PDF Cite