Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 2,665

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.

Exploratory Structural Equation Modeling

Asparouhov, Tihomir, Muthén, Bengt·2009·Structural Equation Modeling: A Multidisciplinary Journal

Abstract

Exploratory factor analysis (EFA) is a frequently used multivariate analysis technique in statistics. Jennrich and Sampson (1966) Jennrich, R. I. and Sampson, P. F. 1966. Rotation to simple loadings.. Psychometrika, 31: 313–323. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar] solved a significant EFA factor loading matrix rotation problem by deriving the direct Quartimin rotation. Jennrich was also the first to develop standard errors for rotated solutions, although these have still not made their way into most statistical software programs. This is perhaps because Jennrich's achievements were partly overshadowed by the subsequent development of confirmatory factor analysis (CFA) by Jöreskog (1969) Jöreskog, K. G. 1969. A general approach to confirmatory maximum-likelihood factor analysis.. Psychometrika, 34: 183–202. [Crossref], [Web of Science ®] , [Google Scholar]. The strict requirement of zero cross-loadings in CFA, however, often does not fit the data well and has led to a tendency to rely on extensive model modification to find a well-fitting model. In such cases, searching for a well-fitting measurement model may be better carried out by EFA (Browne, 2001 Browne, M. W. 2001. An overview of analytic rotation in exploratory factor analysis.. Multivariate Behavioral Research, 36: 111–150. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). Furthermore, misspecification of zero loadings usually leads to distorted factors with over-estimated factor correlations and subsequent distorted structural relations. This article describes an EFA-SEM (ESEM) approach, where in addition to or instead of a CFA measurement model, an EFA measurement model with rotations can be used in a structural equation model. The ESEM approach has recently been implemented in the Mplus program. ESEM gives access to all the usual SEM parameters and the loading rotation gives a transformation of structural coefficients as well. Standard errors and overall tests of model fit are obtained. Geomin and Target rotations are discussed. Examples of ESEM models include multiple-group EFA with measurement and structural invariance testing, test–retest (longitudinal) EFA, EFA with covariates and direct effects, and EFA with correlated residuals. Testing strategies with sequences of EFA and CFA models are discussed. Simulated and real data are used to illustrate the points.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1080/10705510903008204

Cites

39 of 39 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 39 references

Research works printed but not linked: 4

  1. Asparouhov T., 2007, Computing the asymptotic distribution of the rotated solution in exploratory factor analysis using Mplus.
  2. 10.1037/0033-2909.115.3.475 · doi:10.1037/0033-2909.115.3.475 · Paper page
  3. 10.1037/0033-2909.111.3.490 · DOI · Paper page
  4. 10.1207/s15327906mbr2704_5 · doi:10.1207/s15327906mbr2704_5

Cited by

See all 2,665

Metadata

Authors
Asparouhov, T., & Muthén, B.
Venue
Structural Equation Modeling: A Multidisciplinary Journal
Published
2009-07-14
Volume
16
Issue
3
Pages
397-438
ISSN
  • 1070-5511 (ISSN-L)
  • 1532-8007
OpenAlex
W2040890982
Cited by
2,665
References
39
FWCI
67.20
Type
journal article
Language
en
Open access
closed

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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Exploratory Structural Equation Modeling. https://app.cochat.ai/papers/10.1080/10705510903008204
The paper
Asparouhov, T., & Muthén, B. (2009). Exploratory Structural Equation Modeling. Structural Equation Modeling: A Multidisciplinary Journal. https://doi.org/10.1080/10705510903008204

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.