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Investigación confirmatoria asistida por simulación×Análisis Factorial Confirmatorio (AFC)×
CampoDiseño de investigaciónPsicometría
FamiliaProcess / pipelineLatent structure
Año de origen1980s–2000s (widespread integration in behavioral and social sciences)1969
Autor originalNo single originator; tradition formalized through Monte Carlo methods (Metropolis & Ulam, 1949) applied to confirmatory designsKarl Gustav Jöreskog
TipoQuantitative hybrid designHypothesis-testing latent variable model
Fuente seminalMorey, R. D., Chambers, C. D., Aitken, M. R. F., Harris, C. R., Hoekstra, R., Lakens, D., Lewandowsky, S., Morey, C. C., Newman, D. P., Schonbrodt, F. D., Vanpaemel, W., Wagenmakers, E. J., & Zwaan, R. A. (2022). The Peer Reviewers' Openness Initiative: Incentivising open research practices through peer review. Royal Society Open Science, 3(1), 150547. link ↗Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗
Aliassimulation-based confirmatory design, Monte Carlo confirmatory research, computational confirmatory study, simulation-enhanced hypothesis testingCFA, confirmatory FA, measurement model, restricted factor analysis
Relacionados54
ResumenSimulation-assisted confirmatory research integrates computational simulation — most commonly Monte Carlo methods — into a hypothesis-driven, confirmatory study design. Before or alongside empirical data collection, the researcher runs simulated data under specified model assumptions to establish expected parameter distributions, verify statistical power, and anticipate the behavior of the chosen analysis. The empirical findings are then evaluated against those simulation-derived benchmarks, strengthening the evidential value of confirmatory conclusions.Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.
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ScholarGateComparar métodos: Simulation-assisted confirmatory research · Confirmatory factor analysis. Recuperado el 2026-06-18 de https://scholargate.app/es/compare