A structured framework for assessing sensitivity to missing data assumptions in longitudinal clinical trials

Pharmaceutical Statistics

Volumn 12, Issue 1, 2013, Pages 1-6

  Mallinckrodt, C H ^a   Lin, Q ^a   Molenberghs, M ^b,c  

^a ELI LILLY AND COMPANY   (United States)

^b HASSELT UNIVERSITY   (Belgium)

^c UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

clinical trials; missing data; sensitivity analyses

Indexed keywords

PLACEBO;

ARTICLE; CLINICAL TRIAL (TOPIC); DATA SYNTHESIS; HUMAN; MAJOR DEPRESSION; MISSING AT RANDOM; MISSING NOT AT RANDOM; SENSITIVITY ANALYSIS; STATISTICAL ANALYSIS; STATISTICAL MODEL; STRUCTURED FRAMEWORK; TREATMENT OUTCOME;

ANTIDEPRESSIVE AGENTS; BIAS (EPIDEMIOLOGY); CLINICAL TRIALS, PHASE III AS TOPIC; DATA INTERPRETATION, STATISTICAL; DEPRESSION; DOUBLE-BLIND METHOD; HUMANS; LIKELIHOOD FUNCTIONS; LONGITUDINAL STUDIES; MODELS, STATISTICAL; PATIENT DROPOUTS; RANDOMIZED CONTROLLED TRIALS AS TOPIC; RETROSPECTIVE STUDIES; TIME FACTORS; TREATMENT OUTCOME;

EID: 84872486967     PISSN: 15391604     EISSN: 15391612     Source Type: Journal    
DOI: 10.1002/pst.1547     Document Type: Article

References (12)

1. Carpenter J, Roger J, Kenward M,. Analysis of longitudinal trials with missing data: a framework for relevant, accessible assumptions, and inference via multiple imputation. (Accepted for publication).
2. Molenberghs G, Kenward MG,. Missing Data in Clinical Studies. John Wiley & Sons: Chichester, 2007.
3. National Research Council. The Prevention and Treatment of Missing Data in Clinical Trials. Panel on Handling Missing Data in Clinical Trials. Committee on National Statistics, Division of Behavioral and Social Sciences and Education, The National Academies Press: Washington, DC, 2010.
4. Committee for Medicinal Products for Human Use. Guideline on Missing Data in Confirmatory Clinical Trials. European Medicines Agency: London, 2010.
5. Mallinckrodt CH, Lane PW, Schnell D, Peng U, Mancuso JP,. Recommendations for the primary analysis of continuous endpoints in longitudinal clinical trials. Drug Information Journal 2008; 42: 305-319.
6. Goldstein DJ, Lu Y, Detke MJ, Wiltse CG, Mallinckrodt CH, Demitrack MA,. Duloxetine in the treatment of depression: a double-blind placebo-controlled comparison with paroxetine. Journal of Clinical Psychopharmacology 2004; 24 (4): 389-399.
7. Permutt T, Piniero J,. Dealing with the missing data challenge in clinical trials. Drug Information Journal 2009; 43 (4): 449-458.
8. Kim Y,. Missing data handling in chronic pain trials. Journal of Biopharmaceutical Statistics 2011; 21: 2, 311-2, 325.
9. Collins LM, Schafer JL, Kam CM,. A comparison of inclusive and restrictive strategies in modern missing data procedures. Psychological Methods 2001; 6 (4): 330-351.
10. SAS Institute Inc. SAS/STAT® user's guide, Version 9.1. SAS Institute Inc.: Cary, NC, 2003.
11. Rubin DB,. Multiple Imputation for Nonresponse in Surveys. Wiley: New York, 1987.
12. Teshome B, Lipkovich I, Molenberghs G, Mallinckrodt CH,. Placebo multiple imputation: a new approach to sensitivity analyses for incomplete longitudinal clinical trial data. Journal of Biopharmaceutical Statistics Accepted.