A Class of Population Covariance Matrices in the Bootstrap Approach to Covariance Structure Analysis
Datos Bibliográficos
| ID | 19290332 |
|---|---|
| Autores | Ke-Hai Yuan (0000-0003-0610-1745, University of Notre Dame), Kentaro Hayashi (0000-0002-2936-9544, University of Hawaii System), Hirokazu Yanagihara (Hiroshima University) |
| Año | 2007 |
| Volumen | 42 |
| Número | 2 |
| Páginas | 261-281 |
| Fecha de publicación | 2007-06-29 |
| Open Access | No |
| Tipo | ARTICLE |
| Revista | Multivariate Behavioral Research (JOURNAL) |
| Identificadores de la revista | ISSN: 0027-3171 • E-ISSN: 1532-7906 |
| Editorial | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00273170701360662 |
| PMID | 26765488 |
| OpenAlex | W2168993315 |
| Idioma | EN |
| Citas recibidas | 10 |
| Referencias citadas | 50 |
Model evaluation in covariance structure analysis is critical before the results can be trusted. Due to finite sample sizes and unknown distributions of real data, existing conclusions regarding a particular statistic may not be applicable in practice. The bootstrap procedure automatically takes care of the unknown distribution and, for a given sample size, also provides more accurate results than those based on standard asymptotics. But the procedure needs a matrix to play the role of the population covariance matrix. The closer the matrix is to the true population covariance matrix, the more valid the bootstrap inference is. The current paper proposes a class of covariance matrices by combining theory and data. Thus, a proper matrix from this class is closer to the true population covariance matrix than those constructed by any existing methods. Each of the covariance matrices is easy to generate and also satisfies several desired properties. An example with nine cognitive variables and a confirmatory factor model illustrates the details for creating population covariance matrices with different misspecifications. When evaluating the substantive model, bootstrap or simulation procedures based on these matrices will lead to more accurate conclusion than that based on artificial covariance matrices
CMA-ES · Covariance · Covariance function · Covariance intersection · Covariance matrix · Estimation of covariance matrices · Law of total covariance · Matérn covariance function · Matrix (chemical analysis) · Population · Rational quadratic covariance function · Scatter matrix · Statistics · Advanced Statistical Methods and Models · Applied Mathematics · Mathematics · Psychometric Methodologies and Testing · Statistical Methods and Bayesian Inference
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| Citas por año | 0,71 |
|---|---|
| Intervalo de citas | 2012 - 2026 (15) |
| Altamente citado | No |