### Abstract

Reliability can be estimated using structural equation modeling (SEM). Two potential problems with this approach are that estimates may be unstable with small sample sizes and biased with misspecified models. A Monte Carlo study was conducted to investigate the quality of SEM estimates of reliability by themselves and relative to coefficient alpha. The SEM approach showed minimal bias when the model was correctly specified if items were relatively well defined by their underlying factor(s). They tended to demonstrate somewhat greater bias when the model was misspecified, particularly underspecified.Overall, SEMestimates were more stable than anticipated. Researchers are more likely to obtain accurate estimates of reliability using SEM by conducting large-sample studies with well-constructed scales and critically assessing model fit.

Original language | English (US) |
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Pages (from-to) | 66-81 |

Number of pages | 16 |

Journal | Structural Equation Modeling |

Volume | 17 |

Issue number | 1 |

DOIs | |

State | Published - Jan 2010 |

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### ASJC Scopus subject areas

- Modeling and Simulation
- Decision Sciences(all)
- Economics, Econometrics and Finance(all)
- Sociology and Political Science

### Cite this

*Structural Equation Modeling*,

*17*(1), 66-81. https://doi.org/10.1080/10705510903438963

**A note on structural equation modeling estimates of reliability.** / Yang, Yanyun; Green, Samuel B.

Research output: Contribution to journal › Article

*Structural Equation Modeling*, vol. 17, no. 1, pp. 66-81. https://doi.org/10.1080/10705510903438963

}

TY - JOUR

T1 - A note on structural equation modeling estimates of reliability

AU - Yang, Yanyun

AU - Green, Samuel B.

PY - 2010/1

Y1 - 2010/1

N2 - Reliability can be estimated using structural equation modeling (SEM). Two potential problems with this approach are that estimates may be unstable with small sample sizes and biased with misspecified models. A Monte Carlo study was conducted to investigate the quality of SEM estimates of reliability by themselves and relative to coefficient alpha. The SEM approach showed minimal bias when the model was correctly specified if items were relatively well defined by their underlying factor(s). They tended to demonstrate somewhat greater bias when the model was misspecified, particularly underspecified.Overall, SEMestimates were more stable than anticipated. Researchers are more likely to obtain accurate estimates of reliability using SEM by conducting large-sample studies with well-constructed scales and critically assessing model fit.

AB - Reliability can be estimated using structural equation modeling (SEM). Two potential problems with this approach are that estimates may be unstable with small sample sizes and biased with misspecified models. A Monte Carlo study was conducted to investigate the quality of SEM estimates of reliability by themselves and relative to coefficient alpha. The SEM approach showed minimal bias when the model was correctly specified if items were relatively well defined by their underlying factor(s). They tended to demonstrate somewhat greater bias when the model was misspecified, particularly underspecified.Overall, SEMestimates were more stable than anticipated. Researchers are more likely to obtain accurate estimates of reliability using SEM by conducting large-sample studies with well-constructed scales and critically assessing model fit.

UR - http://www.scopus.com/inward/record.url?scp=75149188604&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=75149188604&partnerID=8YFLogxK

U2 - 10.1080/10705510903438963

DO - 10.1080/10705510903438963

M3 - Article

VL - 17

SP - 66

EP - 81

JO - Structural Equation Modeling

JF - Structural Equation Modeling

SN - 1070-5511

IS - 1

ER -