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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Marques, C., Salgueiro, M.F. & Vicente, P.C.R. (2020). Deviations from normality:  Effects on the goodness-of-fit of latent growth curve models. XXVII Meeting of the Portuguese Association of Classification and Data Analysis,.
Exportar Referência (IEEE)
C. M. Marques et al.,  "Deviations from normality:  Effects on the goodness-of-fit of latent growth curve models", in XXVII Meeting of the Portuguese Association of Classification and Data Analysis,, 2020
Exportar BibTeX
@misc{marques2020_1709004205609,
	author = "Marques, C. and Salgueiro, M.F. and Vicente, P.C.R.",
	title = "Deviations from normality:  Effects on the goodness-of-fit of latent growth curve models",
	year = "2020",
	url = "http://www.joclad.ipt.pt/joclad2020/"
}
Exportar RIS
TY  - CPAPER
TI  - Deviations from normality:  Effects on the goodness-of-fit of latent growth curve models
T2  - XXVII Meeting of the Portuguese Association of Classification and Data Analysis,
AU  - Marques, C.
AU  - Salgueiro, M.F.
AU  - Vicente, P.C.R.
PY  - 2020
UR  - http://www.joclad.ipt.pt/joclad2020/
AB  - This study aims to investigate the effect of data deviations from normality on the goodness-of-fit measures in Latent Growth Curve Models (LGCM). Using the VITA method to obtain data generating non-normal distributions, a Monte Carlo simulation study was conducted in order to assess the effects on the values of goodness-of-fit indices. LGCM with unconditional linear growth are considered. Three time points and sample  sizes ranging from 50 to 1000 observations are used. The impacts of such deviations on fit measures are discussed.
ER  -