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Handling Item-Level Missing Data: Simpler Is Just as Good
Abstract
The topic of missing data has been receiving increasing attention, with calls to apply advanced methods of handling missingness to counseling psychology research. The present study sought to assess whether advanced methods of handling item-level missing data performed equivalently to simpler methods in designs similar to those counseling psychologists typically engage in. Results of an initial preliminary analysis, an analysis using real-world data, and a series of simulation studies were used in the present investigation. Results indicated that available case analysis, mean substitution, and multiple imputation had similar results across low levels of missing data, though in data with higher levels of missing data and other problems (e.g., small sample size or scales with weak internal reliability) mean substitution produced inflation of correlation coefficients among items. The present results support the use of available case analysis when dealing with low-level item-level missingness.
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“Item-level missingness was negligible: a single item was missing from the data set, and available item analysis was used to score the scale in this case [56].”
From An Acceptance and Commitment Therapy Prototype Mobile Program for Individuals with a Visible Difference: Mixed Methods Feasibility Study (2022) · cites this paper as [56]
In the citing paper
“Item-level missingness was negligible: a single item was missing from the data set, and available item analysis was used to score the scale in this case [56].”
From An Acceptance and Commitment Therapy Prototype Mobile Program for Individuals with a Visible Difference: Mixed Methods Feasibility Study (2022) · cites this paper as [56]
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Yamasaki, V., & Le, T. P. (2021) · The Journal of Sex Research · doi:10.1080/00224499.2021.1965948 · Cited by 11
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Júnior, M. L. D. O., Almeida, M., Santos, C. G., Brown, T. A., & de Carvalho, P. H. B. (2022) · International Journal of Eating Disorders · doi:10.1002/eat.23853 · Cited by 11
Pine, A. E., Shank, L. M., Burke, N. L., Neyland, M. K. H., Schvey, N. A., Quattlebaum, M. J., Leu, W., Wilfley, D. E., Stephens, M. B., Jorgensen, S., et al. (2020) · American Journal of Psychotherapy · doi:10.1176/appi.psychotherapy.20190034 · Cited by 11
Metadata
- Authors
- Parent, M. C.
- Affiliations
- University of Florida (US)
- Corresponding author
- Parent, Mike C.
- ORCID
- Parent, Mike C.
- Venue
- The Counseling Psychologist
- Publisher
- SAGE Publications
- Published
- 2012-05-10
- Volume
- 41
- Issue
- 4
- Pages
- 568-600
- ISSN
- 0011-0000 (ISSN-L)
- 1552-3861
- OpenAlex
- W2169361290
- Cited by
- 685
- References
- 19
- Citations by year
- 2026: 61 · 2025: 58 · 2024: 74 · 2023: 62 · 2022: 71 · 2021: 63 · 2020: 69 · 2019: 54 · 2018: 32 · 2017: 34 · 2016: 32 · 2015: 34 · 2014: 31 · 2013: 7 · 2012: 1
- FWCI
- 22.34
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Counseling Psychologist (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
- Keywords
- missing data handling, available case analysis, mean substitution, multiple imputation, counseling psychology research, simulation study, internal consistency, small sample size
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