ArticleMultivariate behavioral research2015
Addressing Item-Level Missing Data: A Comparison of Proration and Full Information Maximum Likelihood Estimation.
Article in Multivariate behavioral research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
83 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Modeling the Impact of Race, Socioeconomic Status, Discrimination and Cognitive Appraisal on Mental Health Concerns Among Heavy Drinking HIV+ Cisgender MSM.AIDS and behavior · 2022Trial
- Age and Sexual Orientation Moderated the Effects of a Bystander-Focused Interpersonal Violence Prevention Program for High School Students.Prevention science : the official journal of the Society for Prevention Research · 2022Trial
- Pre-Existing Comorbid Emotional Symptoms Moderate Short-Term Methylphenidate Adverse Effects in a Randomized Trial of Children with Attention-Deficit/Hyperactivity Disorder.Journal of child and adolescent psychopharmacology · 2020Trial
- Evaluation of a Bystander-Focused Interpersonal Violence Prevention Program with High School Students.Prevention science : the official journal of the Society for Prevention Research · 2019Trial
- The Effect of Missing Item Data on the Relative Predictive Accuracy of Intimate Partner Violence Risk Assessment Tools.Assessment · 2026Article
- Including auxiliary cases to address missing data issues through multiple-group models.Behavior research methods · 2026Article
- Pesticide exposure and multidomain symptom burden in Parkinson's disease: a longitudinal triangulation study.NPJ Parkinson's disease · 2026Article
- Identifying Unique Subgroups of Emotional and Behavioral Presentations in a Large Inpatient and Community Sample of Autistic Youth.Autism research : official journal of the International Society for Autism Research · 2026Article
- Fitting in or Not Fitting in: Cultural Congruity as a Correlate of Motivation for Intergroup Contact.Behavioral sciences (Basel, Switzerland) · 2026Article
- Psychological resilience in patients with Friedreich ataxia: a 6-year longitudinal analysis.Neurological research and practice · 2026Article
- Observational
- Random Forest Predicts Human Ratings of Creative Stories Using Very Small Training Samples.Behavioral sciences (Basel, Switzerland) · 2026Article
- Resilience and physical-functional HRQoL in cirrhosis: a cross-sectional study of nursing-relevant direct and indirect associations linked to psychological distress and frailty.Scientific reports · 2026Article
- A survey of knowledge, experiences, and quality of life impacts related to urinary tract infections among people with neurogenic bladder.The journal of spinal cord medicine · 2026Article
- Adolescent Math Anxiety: Teachers' Grouping Approach at the Intersection of Multiple Student Identities.Educational policy (Los Altos, Calif.) · 2026Article
- Article
- Development and Psychometric Evaluation of the Thriving in Nursing Questionnaire (THINQ).Journal of advanced nursing · 2026Article
23 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Often when participants have missing scores on one or more of the items comprising a scale, researchers compute prorated scale scores by averaging the available items. Methodologists have cautioned that proration may make strict assumptions about the mean and covariance structures of the items comprising the scale (Schafer & Graham, 2002 ; Graham, 2009 ; Enders, 2010 ). We investigated proration empirically and found that it resulted in bias even under a missing completely at random (MCAR) mechanism. To encourage researchers to forgo proration, we describe a full information maximum likelihood (FIML) approach to item-level missing data handling that mitigates the loss in power due to missing scale scores and utilizes the available item-level data without altering the substantive analysis. Specifically, we propose treating the scale score as missing whenever one or more of the items are missing and incorporating items as auxiliary variables. Our simulations suggest that item-level missing data handling drastically increases power relative to scale-level missing data handling. These results have important practical implications, especially when recruiting more participants is prohibitively difficult or expensive. Finally, we illustrate the proposed method with data from an online chronic pain management program.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.