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Cited by 5,497Psychometric Methodologies and TestingStatistical Methods and ApplicationsStatistical Methods and Bayesian Inference

The DOI matches its Crossref record; 49 of the 50 references it cites were found in a registry or an index.

Sample size in factor analysis.

MacCallum, Robert C., Widaman, Keith F., Zhang, Shaobo, Hong, Sehee·1999·Psychological Methods
DOI 10.1037/1082-989x.4.1.84
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Abstract

The factor analysis literature includes a range of recommendations regarding the minimum sample size necessary to obtain factor solutions that are adequately stable and that correspond closely to population factors. A fundamental misconception about this issue is that the minimum sample size, or the minimum ratio of sample size to the number of variables, is invariant across studies. In fact, necessary sample size is dependent on several aspects of any given study, including the level of communality of the variables and the level of overdetermination of the factors. The authors present a theoretical and mathematical framework that provides a basis for understanding and predicting these effects. The hypothesized effects are verified by a sampling study using artificial data. Results demonstrate the lack of validity of common rules of thumb and provide a basis for establishing guidelines for sample size in factor analysis. In the factor analysis literature, much attention has be;;n given to the issue of sample size. It is widely understood that the use of larger samples in applica-tions of factor analysis tends to provide results such that sample factor loadings are more precise estimates of population loadings and are also more stable, or les s variable, across repeated sampling. Despite gen-eral agreement on this matter, there is considerable di'/ergence of opinion and evidence about the ques-tion of how large a sample is necessary to adequately acnieve these objectives. Recommendations and find-ings about this issue are diverse and often contradic-tory. The objectives of this article are to provide a

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Crossref · 10.1037/1082-989x.4.1.84

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49 of 49 references verified0 citation errors · 0 not checkable

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  • The number of participants needed for a stable factor solution depends jointly on how many factors there are, how many items load on each factor, and how strong the loadings are.

    “recent simulations show that the sample size required to recover a stable factor structure is a joint function of number of factors, number of items per factor (with the required sample size stabilizing after 6–10 items per factor), and strength of factor loadings (MacCallum et al., 1999; Mundfrom et al., 2005).”

    From The structure of adult ADHD. (2017) · cites this paper as MacCallum et al., 1999

  • SEM flexibility allowing examination of complex associations, multiple data types, model and/or group comparisons makes developing general rules regarding sample size requirements impractical.

    “Additionally, SEM flexibility allowing the examination of complex associations, multiple data types, model and/or group comparisons thus, developing general rules regarding sample size requirements are impractical (MacCallum et al., 1999; Wolf et al., 2013).”

    From Applied Psychometrics: Sample Size and Sample Power Considerations in Factor Analysis (EFA, CFA) and SEM in General (2018) · cites this paper as MacCallum et al., 1999

  • The final sample size of 279 matched questionnaires is in line with sample sizes in other strategy studies and exceeds common recommendations for advanced statistical analyses.

    “While this sample size may not be considered very large, it is much in line with sample sizes in other strategy studies (Phelan, Ferreira, and Salvador, 2002) and exceeds common recommendations for advanced statistical analyses (e.g., MacCallum et al., 1999).”

    From On the contingent value of dynamic capabilities for competitive advantage: The nonlinear moderating effect of environmental dynamism (2014) · cites this paper as MacCallum et al., 1999

  • The study aimed to reach at least 150 patients based on the rule of at least 5-10 participants per item.

    “According to this rule, data collection process was initiated with the aim of reaching at least 150 patients, which is five times of 30 questions.”

    From Turkish Translation of the Patterns of Activity Measure-Pain in Patients with Chronic Low Back and Neck Pain: Validity and Reliability. (2022) · cites this paper as MacCallum et al., 1999

  • For Study 2, the sample size target was approximately 300 participants per technology, following MacCallum et al. (1999) and Schönbrodt and Perugini (2013).

    “We therefore followed the recommendations of MacCallum et al. (1999) and Schönbrodt and Perugini (2013) and aimed to collect data from ~300 participants using each technology.”

    From Technology evaluations are associated with psychological need satisfaction across different spheres of experience: an application of the METUX scales (2023) · cites this paper as MacCallum et al., 1999

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Metadata

Authors
MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S.
Affiliations
  • The Ohio State University (US)
  • University of California, Riverside (US)
ORCID
Venue
Psychological Methods
Publisher
American Psychological Association (APA)
Published
1999-03
Volume
4
Issue
1
Pages
84-99
ISSN
  • 1082-989X (ISSN-L)
  • 1939-1463
DOI
10.1037/1082-989x.4.1.84
OpenAlex
W2122376319
Cited by
5,497
References
50
Citations by year
2026: 456 · 2025: 418 · 2024: 359 · 2023: 311 · 2022: 359 · 2021: 396 · 2020: 413 · 2019: 318 · 2018: 286 · 2017: 276 · 2016: 259 · 2015: 226 · 2014: 230 · 2013: 233 · 2012: 177
FWCI
27.00
Type
journal article
Language
en
Open access
closed
Locations
Psychological Methods (publishedVersion)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords
sample size, factor analysis, minimum sample size, communality, rules of thumb

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