ISBN: 9783659411915 - effects of ignoring clustered data structures in factor analysis: with applications to psychiatry (5 resultados)

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2013

    3659411914 / 9783659411915

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    Taschenbuch. Condición: Neu. Effects of Ignoring Clustered Data Structures in Factor Analysis | with Applications to Psychiatry | Jan Stochl | Taschenbuch | 100 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659411915 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

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    Editorial: LAP LAMBERT Academic Publishing Jun 2013, 2013

    3659411914 / 9783659411915

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In psychiatric research, data for analysis originate principally from two sources: directly from the patients themselves and from interviews conducted by health care professionals. In the latter case, statistical theory indicates that clustering by interviewers or raters needs to be considered when performing any analyses including regression, factor analysis (FA) or item response theory (IRT) modelling of binary or ordinal data. We use simulated data to study the bias of factor analytic estimates and model fit indices when data clustering is fully or partly ignored. Robustness of different estimators, such as maximum likelihood, weighted least squares and Markov chain Monte Carlo is also presented. In the second part, we analyse two real datasets containing responses to the Positive and Negative Syndrome Scale (PANSS) to show the differences when the data are analysed using the correct multilevel approach rather than a traditional aggregated analysis. 100 pp. Englisch. …

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    Editorial: LAP LAMBERT Academic Publishing, 2013

    3659411914 / 9783659411915

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In psychiatric research, data for analysis originate principally from two sources: directly from the patients themselves and from interviews conducted by health care professionals. In the latter case, statistical theory indicates that clustering by interviewers or raters needs to be considered when performing any analyses including regression, factor analysis (FA) or item response theory (IRT) modelling of binary or ordinal data. We use simulated data to study the bias of factor analytic estimates and model fit indices when data clustering is fully or partly ignored. Robustness of different estimators, such as maximum likelihood, weighted least squares and Markov chain Monte Carlo is also presented. In the second part, we analyse two real datasets containing responses to the Positive and Negative Syndrome Scale (PANSS) to show the differences when the data are analysed using the correct multilevel approach rather than a traditional aggregated analysis. …

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    Editorial: LAP LAMBERT Academic Publishing, 2013

    3659411914 / 9783659411915

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    Librería: moluna, Greven, Alemaniamoluna

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    EUR 26,80

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    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Stochl JanJan Stochl is a Research Associate in the Department of Psychiatry at the University of Cambridge and Associate Professor at Charles University in the Czech Republic. His specialization is in statistical modellingwith laten.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Jun 2013, 2013

    3659411914 / 9783659411915

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In psychiatric research, data for analysis originate principally from two sources: directly from the patients themselves and from interviews conducted by health care professionals. In the latter case, statistical theory indicates that clustering by interviewers or raters needs to be considered when performing any analyses including regression, factor analysis (FA) or item response theory (IRT) modelling of binary or ordinal data. We use simulated data to study the bias of factor analytic estimates and model fit indices when data clustering is fully or partly ignored. Robustness of different estimators, such as maximum likelihood, weighted least squares and Markov chain Monte Carlo is also presented. In the second part, we analyse two real datasets containing responses to the Positive and Negative Syndrome Scale (PANSS) to show the differences when the data are analysed using the correct multilevel approach rather than a traditional aggregated analysis.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 100 pp. Englisch. …