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Articles

Implications of Missing Data Mechanisms in Randomized Controlled Trials: Current Practices and Suggestions Utilizing the ACTIVE Study

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By Jody S. Nicholson, Pascal R. Deboeck, Waylon Howard
| Wiley Online Library Verified
1 Introduction Missing data have the potential to skew inferences made from randomized controlled trials (RCTs). Modern missing data tools (i.e., full information maximum likelihood (FIML), multiple imputation (MI)) can produce unbiased inferences under specific conditions, and help evaluate the validity of inferences on missing data assumptions [1, 2]. The application of modern methods for missing data differs depending on the mechanism that produces missing data [3, 4].
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Aberrant behavior checklist in youth with Prader-Willi syndrome: Preliminary study of cross‐sectional and longitudinal behavior characterization

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By Soo-Jeong Kim, Lydia Kim, Waylon Howard, Bridget McNulty
| pericles.pericles-prod.literatumonline.com
CONFLICT OF INTEREST STATEMENT The authors declare no conflicts of interest. REFERENCES , , , & (1985a). The aberrant behavior checklist: A behavior rating scale for the assessment of treatment effects. American Journal of Mental Deficiency, 89(5), 485–491. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=3993694 , , , & (1985b). Psychometric characteristics of the aberrant behavior checklist. American Journal of Mental Deficiency, 89(5), 492–502.
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