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PUBMED FOR HANDHELDS

Journal Abstract Search

252 related items for PubMed ID: 16942125

  • 1. Missing data imputation in quality-of-life assessment: imputation for WHOQOL-BREF.
    Lin TH.
    Pharmacoeconomics; 2006; 24(9):917-25. PubMed ID: 16942125
    [Abstract] [Full Text] [Related]

  • 2. Missing data on the Center for Epidemiologic Studies Depression Scale: a comparison of 4 imputation techniques.
    Bono C, Ried LD, Kimberlin C, Vogel B.
    Res Social Adm Pharm; 2007 Mar; 3(1):1-27. PubMed ID: 17350555
    [Abstract] [Full Text] [Related]

  • 3. Devising a Missing Data Rule for a Quality of Life Questionnaire-A Simulation Study.
    Jacoby P, Whitehouse A, Leonard H, Saldaris J, Demarest S, Benke T, Downs J.
    J Dev Behav Pediatr; 2022 Aug 01; 43(6):e414-e418. PubMed ID: 35075044
    [Abstract] [Full Text] [Related]

  • 4. Sequential Multiple Imputation for Real-World Health-Related Quality of Life Missing Data after Bariatric Surgery.
    Sun S, Luo N, Stenberg E, Lindholm L, Sahlén KG, Franklin KA, Cao Y.
    Int J Environ Res Public Health; 2022 Aug 30; 19(17):. PubMed ID: 36078543
    [Abstract] [Full Text] [Related]

  • 5. Missing item imputation for quality-of-life instruments with application to asthma quality-of-life questionnaires.
    Wang J, Rapatz G, Lowy A, Olson S, Kuebler J.
    Pharm Stat; 2009 Aug 30; 8(1):73-83. PubMed ID: 18383560
    [Abstract] [Full Text] [Related]

  • 6. Comparing methods for handling missing values in food-frequency questionnaires and proposing k nearest neighbours imputation: effects on dietary intake in the Norwegian Women and Cancer study (NOWAC).
    Parr CL, Hjartåker A, Scheel I, Lund E, Laake P, Veierød MB.
    Public Health Nutr; 2008 Apr 30; 11(4):361-70. PubMed ID: 17601360
    [Abstract] [Full Text] [Related]

  • 7. Ipsative imputation for a 15-item Geriatric Depression Scale in community-dwelling elderly people.
    Imai H, Furukawa TA, Kasahara Y, Ishimoto Y, Kimura Y, Fukutomi E, Chen WL, Tanaka M, Sakamoto R, Wada T, Fujisawa M, Okumiya K, Matsubayashi K.
    Psychogeriatrics; 2014 Sep 30; 14(3):182-7. PubMed ID: 25323959
    [Abstract] [Full Text] [Related]

  • 8. Multiple imputation for patient reported outcome measures in randomised controlled trials: advantages and disadvantages of imputing at the item, subscale or composite score level.
    Rombach I, Gray AM, Jenkinson C, Murray DW, Rivero-Arias O.
    BMC Med Res Methodol; 2018 Aug 28; 18(1):87. PubMed ID: 30153796
    [Abstract] [Full Text] [Related]

  • 9. Imputation of SF-12 health scores for respondents with partially missing data.
    Liu H, Hays RD, Adams JL, Chen WP, Tisnado D, Mangione CM, Damberg CL, Kahn KL.
    Health Serv Res; 2005 Jun 28; 40(3):905-21. PubMed ID: 15960697
    [Abstract] [Full Text] [Related]

  • 10. Passive imputation and parcel summaries are both valid to handle missing items in studies with many multi-item scales.
    Eekhout I, de Vet HC, de Boer MR, Twisk JW, Heymans MW.
    Stat Methods Med Res; 2018 Apr 28; 27(4):1128-1140. PubMed ID: 27334917
    [Abstract] [Full Text] [Related]

  • 11. Imputation strategies when a continuous outcome is to be dichotomized for responder analysis: a simulation study.
    Floden L, Bell ML.
    BMC Med Res Methodol; 2019 Jul 23; 19(1):161. PubMed ID: 31345166
    [Abstract] [Full Text] [Related]

  • 12. The multiple imputation method: a case study involving secondary data analysis.
    Walani SR, Cleland CM.
    Nurse Res; 2015 May 23; 22(5):13-9. PubMed ID: 25976532
    [Abstract] [Full Text] [Related]

  • 13. Imputation of missing values within WHODAS 2.0 data collected from low back pain patients using the response function approach.
    Siddikoglu D, Doganay Erdogan B, Gokmen D, Kutlay S.
    Disabil Rehabil; 2023 Aug 23; 45(17):2837-2844. PubMed ID: 35961290
    [Abstract] [Full Text] [Related]

  • 14. A simple imputation algorithm reduced missing data in SF-12 health surveys.
    Perneger TV, Burnand B.
    J Clin Epidemiol; 2005 Feb 23; 58(2):142-9. PubMed ID: 15680747
    [Abstract] [Full Text] [Related]

  • 15. PROMIS Global Health item nonresponse: is it better to impute missing item responses before computing T-scores?
    Thompson NR, Katzan IL, Honomichl RD, Lapin BR.
    Qual Life Res; 2020 Feb 23; 29(2):537-546. PubMed ID: 31630291
    [Abstract] [Full Text] [Related]

  • 16. Missing data methods for dealing with missing items in quality of life questionnaires. A comparison by simulation of personal mean score, full information maximum likelihood, multiple imputation, and hot deck techniques applied to the SF-36 in the French 2003 decennial health survey.
    Peyre H, Leplège A, Coste J.
    Qual Life Res; 2011 Mar 23; 20(2):287-300. PubMed ID: 20882358
    [Abstract] [Full Text] [Related]

  • 17. The ability of different imputation methods for missing values in mental measurement questionnaires.
    Xu X, Xia L, Zhang Q, Wu S, Wu M, Liu H.
    BMC Med Res Methodol; 2020 Feb 27; 20(1):42. PubMed ID: 32103723
    [Abstract] [Full Text] [Related]

  • 18. Dealing with missing data in a multi-question depression scale: a comparison of imputation methods.
    Shrive FM, Stuart H, Quan H, Ghali WA.
    BMC Med Res Methodol; 2006 Dec 13; 6():57. PubMed ID: 17166270
    [Abstract] [Full Text] [Related]

  • 19. A Comparison of Missing-Data Imputation Techniques in Exploratory Factor Analysis.
    Xiao C, Bruner DW, Dai T, Guo Y, Hanlon A.
    J Nurs Meas; 2019 Aug 01; 27(2):313-334. PubMed ID: 31511412
    [Abstract] [Full Text] [Related]

  • 20. Simple imputation methods versus direct likelihood analysis for missing item scores in multilevel educational data.
    Kadengye DT, Cools W, Ceulemans E, Van den Noortgate W.
    Behav Res Methods; 2012 Jun 01; 44(2):516-31. PubMed ID: 22002637
    [Abstract] [Full Text] [Related]

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