Regression Among Factor Scores
Bibliographic Data
| ID | 23328748 |
|---|---|
| Authors | Anders Skrondal (0000-0002-8171-2282, Department of Epidemiology, National Institute of Public Health, corresponding author), Petter Laake (Section of Medical Statistics, University of Oslo) |
| Year | 2001 |
| Volume | 66 |
| Issue | 4 |
| Pages | 563-575 |
| Publication date | 2001-12-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Psychometrika (JOURNAL) |
| Journal identifiers | ISSN: 0033-3123 • E-ISSN: 1860-0980 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1007/bf02296196 |
| OpenAlex | W2000301050 |
| Language | EN |
| Citations received | 142 |
| References cited | 22 |
Structural equation models with latent variables are sometimes estimated using an intuitive three-step approach, here denoted factor score regression. Consider a structural equation model composed of an explanatory latent variable and a response latent variable related by a structural parameter of scientific interest. In this simple example estimation of the structural parameter proceeds as follows: First, common factor models are separately estimated for each latent variable. Second, factor scores are separately assigned to each latent variable, based on the estimates. Third, ordinary linear regression analysis is performed among the factor scores producing an estimate for the structural parameter. We investigate the asymptotic and finite sample performance of different factor score regression methods for structural equation models with latent variables. It is demonstrated that the conventional approach to factor score regression performs very badly. Revised factor score regression, using Regression factor scores for the explanatory latent variables and Bartlett scores for the response latent variables, produces consistent estimators for all parameters.
Econometrics · Estimator · Factor analysis · Factor regression model · Latent class model · Latent variable · Latent variable model · Linear regression · Local independence · Polynomial regression · Proper linear model · Regression · Regression analysis · Regression diagnostic · Simple linear regression · Statistics · Structural equation modeling · Advanced Statistical Modeling Techniques · Mathematics · Psychometric Methodologies and Testing · Sensory Analysis and Statistical Methods
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| Unique citing works | 142 |
|---|---|
| Citations per year | 5,46 |
| Citation span | 2000 - 2026 (27) |
| Citation velocity | current |
| Highly cited | Yes |
| Citation types | Neutral: 136 |