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Multivariate Explanatory Research — Explaining Outcomes Through Multiple Variables

Multivariate explanatory research is a quantitative design that simultaneously examines multiple independent variables to explain variance in one or more outcomes. Rather than describing what exists or simply correlating pairs of variables, it seeks causal or structural explanations by testing theoretically grounded models with techniques such as multiple regression, MANOVA, or structural equation modeling on survey, administrative, or observational numeric data.

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Sources

  1. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540
  2. Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Sage. ISBN: 978-1452226101

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Referenced by

ScholarGateMultivariate Explanatory Research (Multivariate Explanatory Research Design). Retrieved 2026-06-04 from https://scholargate.app/en/research-design/multivariate-explanatory-research