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                <text>The effects of sampling error and model characteristics on parameter estimation for maximum likelihood confirmatory factor analysis</text>
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                <text>Multivariate Behavioral Research</text>
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                <text>Parent caregivers; Factor Analysis; MONTE Carlo method; SAMPLING (Statistics)</text>
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                <text>Monte Carlo methods were used to systematically study the effects of sampling error and model characteristics upon parameter estimates and their associated standard errors in maximum likelihood confirmatory factor analysis. Sample sizes were varied from 50 to 300 for models defined by different numbers of indicators per factor, numbers of factors, correlations between factors, and indicator reliabilities. The measurement and structural parameter estimates were generally unbiased except for the structural parameters relating factors defined by only two indicators. Sampling variability can be quite large, though, particularly as sample size becomes smaller, there are fewer indicators per factor and the reliabilities are lower. However, the estimated standard errors were adjusted accordingly. [ABSTRACT FROM AUTHOR]; Copyright of Multivariate Behavioral Research is the property of Lawrence Erlbaum Associates and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts)</text>
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