Comparar métodos

	Pesquisa de Teste de Modelos Multivariados	Análise de Caminhos
Área	Delineamento de pesquisa	Estatística
Família	Process / pipeline	Latent structure
Ano de origem	1970s–1980s (multivariate model testing as a distinct approach)	1921
Autor original	Karl Jöreskog (SEM/LISREL framework); Barbara Tabachnick & Linda Fidell (multivariate methods synthesis)	Sewall Wright
Tipo	Quantitative confirmatory research design	Causal / mediation model
Fonte seminal	Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541	Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20(7), 557–585.
Outros nomes	multivariate model testing, multivariate structural testing, multivariate confirmatory modeling, MVMT research	PA, path coefficient analysis, observed-variable SEM, causal path modeling
Relacionados	5	5
Resumo	Multivariate model testing research is a confirmatory quantitative design in which a theoretically derived model involving multiple variables and their interrelationships is formally tested against empirical data. Rather than exploring patterns inductively, the researcher specifies a model a priori — capturing hypothesized directional paths, latent constructs, or covariance structures — and then evaluates how well this model reproduces the observed data using techniques such as structural equation modeling, confirmatory factor analysis, or multivariate path analysis.	Path analysis tests a researcher-specified causal diagram among observed variables by decomposing their intercorrelations into direct effects, indirect (mediated) effects, and spurious associations. Developed by Sewall Wright in 1921, it is the observed-variable special case of structural equation modeling and remains a standard tool for theory-driven multivariate causal inference.