Literature DB >> 12704618

A method for comparing two normal means using combined samples of correlated and uncorrelated data.

Stephen W Looney1, Peter W Jones.   

Abstract

A method is proposed for comparing two normal means when the data consist of some observations that are correlated and others that are uncorrelated. Typically, such data will consist of one subsample in which the observations for treatment 1 and treatment 2 are independent of each other, and another subsample which consists of paired observations taken under both treatments. The proposed method is developed using asymptotic results and is evaluated using simulation. The simulation results indicate that the proposed method can provide substantial improvement in type I error rate and power when compared with standard methods of analysis. Copyright 2003 John Wiley & Sons, Ltd.

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Year:  2003        PMID: 12704618     DOI: 10.1002/sim.1514

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  6 in total

1.  Children's reasoning about disclosing adult transgressions: effects of maltreatment, child age, and adult identity.

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2.  A simple and robust method for partially matched samples using the p-values pooling approach.

Authors:  Pei Fen Kuan; Bo Huang
Journal:  Stat Med       Date:  2013-02-17       Impact factor: 2.373

3.  Analyzing partially paired data: when can the unpaired portion(s) be safely ignored?

Authors:  Qianya Qi; Li Yan; Lili Tian
Journal:  J Appl Stat       Date:  2020-12-23       Impact factor: 1.416

4.  Optimal weighted two-sample t-test with partially paired data in a unified framework.

Authors:  Xu Guo; Yan Wang; Niwen Zhou; Xuehu Zhu
Journal:  J Appl Stat       Date:  2020-04-20       Impact factor: 1.416

Review 5.  Propensity score method for partially matched omics studies.

Authors:  Pei-Fen Kuan
Journal:  Cancer Inform       Date:  2014-10-29

6.  Intracellular and extracellular redox status and free radical generation in primary immune cells from children with autism.

Authors:  Shannon Rose; Stepan Melnyk; Timothy A Trusty; Oleksandra Pavliv; Lisa Seidel; Jingyun Li; Todd Nick; S Jill James
Journal:  Autism Res Treat       Date:  2011-11-24
  6 in total

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