The Effect of Sampling-Time Variation on Latent Growth Curve Models
Longitudinal data are often collected in waves in which a participant's data can be collected at different times within each wave, resulting in sampling-time variation that is unaccounted for when waves are treated as single time points. Little research has been reported on the effects of this...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Miller, Matt L [verfasserIn] |
|---|
| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Rechteinformationen: |
Nutzungsrecht: Copyright © Taylor & Francis Group, LLC |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Structural equation modeling - Philadelphia, Pa. : Psychology Press, Taylor & Francis Group, 1994, 24(2017), 6, Seite 831 |
|---|---|
| Übergeordnetes Werk: |
volume:24 ; year:2017 ; number:6 ; pages:831 |
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| DOI / URN: |
10.1080/10705511.2017.1346476 |
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| 520 | |a Longitudinal data are often collected in waves in which a participant's data can be collected at different times within each wave, resulting in sampling-time variation that is unaccounted for when waves are treated as single time points. Little research has been reported on the effects of this temporal imprecision on longitudinal growth-curve modeling. This article describes the results of a simulation study into the effect of sampling-time variation on parameter estimation, model fit, and model comparison with an empirical validation of the model fit and comparison results. | ||
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Longitudinal data are often collected in waves in which a participant's data can be collected at different times within each wave, resulting in sampling-time variation that is unaccounted for when waves are treated as single time points. Little research has been reported on the effects of this temporal imprecision on longitudinal growth-curve modeling. This article describes the results of a simulation study into the effect of sampling-time variation on parameter estimation, model fit, and model comparison with an empirical validation of the model fit and comparison results. |
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Longitudinal data are often collected in waves in which a participant's data can be collected at different times within each wave, resulting in sampling-time variation that is unaccounted for when waves are treated as single time points. Little research has been reported on the effects of this temporal imprecision on longitudinal growth-curve modeling. This article describes the results of a simulation study into the effect of sampling-time variation on parameter estimation, model fit, and model comparison with an empirical validation of the model fit and comparison results. |
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Longitudinal data are often collected in waves in which a participant's data can be collected at different times within each wave, resulting in sampling-time variation that is unaccounted for when waves are treated as single time points. Little research has been reported on the effects of this temporal imprecision on longitudinal growth-curve modeling. This article describes the results of a simulation study into the effect of sampling-time variation on parameter estimation, model fit, and model comparison with an empirical validation of the model fit and comparison results. |
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The Effect of Sampling-Time Variation on Latent Growth Curve Models |
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http://dx.doi.org/10.1080/10705511.2017.1346476 http://www.tandfonline.com/doi/abs/10.1080/10705511.2017.1346476 https://search.proquest.com/docview/1947024746 |
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false |
| author2 |
Ferrer, Emilio |
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Ferrer, Emilio |
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188644075 |
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| doi_str |
10.1080/10705511.2017.1346476 |
| up_date |
2024-07-04T04:45:13.040Z |
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1803622351406891008 |
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