Work

What You Don't Know Can Hurt You: Missing Data and Partial Credit Model Estimates.

Year: 2016

Type: article

Abstract: The authors investigated the effect of missing completely at random (MCAR) item responses on partial credit model (PCM) parameter estimates in a longitudinal study of Positive Affect. Participants were 307 adults from the older cohort of the Notre Dame Study of Health and Well-Being (Bergeman and Deboeck, 2014) who completed questionnaires including Positive Affect items for 56 days. Additional missing responses were introduced to the data, randomly replacing 20%, 50%, and 70% of the responses on each item and each day with missing values, in addition to the existing missing data. Results indicated that item locations and person trait level measures diverged from the original estimates as the level of degradation from induced missing data increased. In addition, standard errors of these estimates increased with the level of degradation. Thus, MCAR data does damage the quality and precision of PCM estimates.

Source: PubMed

Authors: Sarah L Thomas, Karen M Schmidt, Monica K Erbacher, Cindy S Bergeman

Institution: University of Virginia

Language: English

Topic: Psychometric Methodologies and Testing

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: green

Funder: National Institute on Aging

Award: Notre Dame Study of Health & Well-being

OpenAlex ID: W2462838919

FWCI: 0.311

Cites: 9

Cited by: 3

Related to: 10