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Journal Abstract Search

536 related items for PubMed ID: 24210708

  • 1. Missing data in longitudinal studies: cross-sectional multiple imputation provides similar estimates to full-information maximum likelihood.
    Ferro MA.
    Ann Epidemiol; 2014 Jan; 24(1):75-7. PubMed ID: 24210708
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  • 2. On the joys of missing data.
    Little TD, Jorgensen TD, Lang KM, Moore EW.
    J Pediatr Psychol; 2014 Mar; 39(2):151-62. PubMed ID: 23836191
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  • 3. Attrition in longitudinal studies. How to deal with missing data.
    Twisk J, de Vente W.
    J Clin Epidemiol; 2002 Apr; 55(4):329-37. PubMed ID: 11927199
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  • 5. Application of pattern mixture models to address missing data in longitudinal data analysis using SPSS.
    Son H, Friedmann E, Thomas SA.
    Nurs Res; 2012 Apr; 61(3):195-203. PubMed ID: 22551994
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  • 6. Handling missing data in self-report measures.
    Fox-Wasylyshyn SM, El-Masri MM.
    Res Nurs Health; 2005 Dec; 28(6):488-95. PubMed ID: 16287052
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  • 7. Multiple imputation of missing values was not necessary before performing a longitudinal mixed-model analysis.
    Twisk J, de Boer M, de Vente W, Heymans M.
    J Clin Epidemiol; 2013 Sep; 66(9):1022-8. PubMed ID: 23790725
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  • 9. A semi-parametric shared parameter model to handle nonmonotone nonignorable missingness.
    Tsonaka R, Verbeke G, Lesaffre E.
    Biometrics; 2009 Mar; 65(1):81-7. PubMed ID: 18373713
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  • 10. Missing data analysis: making it work in the real world.
    Graham JW.
    Annu Rev Psychol; 2009 Mar; 60():549-76. PubMed ID: 18652544
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  • 11. Missing not at random models for latent growth curve analyses.
    Enders CK.
    Psychol Methods; 2011 Mar; 16(1):1-16. PubMed ID: 21381816
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  • 13. Model selection of generalized estimating equations with multiply imputed longitudinal data.
    Shen CW, Chen YH.
    Biom J; 2013 Nov; 55(6):899-911. PubMed ID: 23970494
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  • 20. Analyzing longitudinal data with missing values.
    Enders CK.
    Rehabil Psychol; 2011 Nov; 56(4):267-88. PubMed ID: 21967118
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