CoChat
Sign Up
Cited by 344Statistical Methods and Bayesian InferencePsychometric Methodologies and TestingSurvey Methodology and Nonresponse

Missing Data in Multiple Item Scales: A Monte Carlo Analysis of Missing Data Techniques

Roth, Philip L., Switzer, Fred S., Switzer, Deborah M.·1999·Organizational Research Methods
DOI 10.1177/109442819923001
Open this paper in CoChat — free account

Abstract

Researchers in many fields use multiple item scales to measure important variables such as attitudes and personality traits, but find that some respondents failed to complete certain items. Past missing data research focuses on missing entire instruments, and is of limited help because there are few variables to help impute missing scores and the variables are often not highly related to each other. Multiple item scales offer the unique opportunity to impute missing values from other correlated items designed to measure the same construct. A Monte Carlo analysis was conducted to compare several missing data techniques. The techniques included listwise deletion, regression imputation, hot-deck imputation, and two forms of mean substitution. Results suggest that regression imputation and substituting the mean response of a person to other items on a scale are very promising approaches. Furthermore, the imputation techniques often outperformed listwise deletion.

Integrity signals

Registry

Crossref · 10.1177/109442819923001

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Missing data for PSWQ, IES-R, and DASS-21 were handled by individual mean substitution up to a maximum of 30% of missing items, with less than 1% of data replaced.

    “For the PSWQ, IES-R and DASS-21, individual mean substitution was used up to a maximum of 30% of missing items (Roth et al., 1999). Less than 1% of data was replaced using this approach.”

    From Parental Anxiety and Posttraumatic Stress Symptoms in Pediatric Food Allergy. (2021) · cites this paper as Roth et al., 1999

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Roth, P. L., Switzer, F. S., & Switzer, D. M.
Affiliations
Clemson University (US)
ORCID
Venue
Organizational Research Methods
Publisher
SAGE Publications
Published
1999-07
Volume
2
Issue
3
Pages
211-232
ISSN
  • 1094-4281 (ISSN-L)
  • 1552-7425
DOI
10.1177/109442819923001
OpenAlex
W2122169890
Cited by
344
References
39
Citations by year
2026: 5 · 2025: 7 · 2024: 11 · 2023: 8 · 2022: 17 · 2021: 14 · 2020: 16 · 2019: 20 · 2018: 28 · 2017: 17 · 2016: 15 · 2015: 19 · 2014: 19 · 2013: 21 · 2012: 26
FWCI
2.99
Type
journal article
Language
en
Open access
closed
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations
Organizational Research Methods (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, regression imputation, hot deck imputation, mean substitution, listwise deletion, imputation accuracy, attitudes, personality traits

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review