Don`t leave things half done. Regression model diagnostics.
DOI:
https://doi.org/10.30445/rear.v13i7.966Keywords:
lineal regression, regression model diagnostics, linearity, homocedasticity, normality, independenceAbstract
Once we obtain the simple linear regression model, we have to proceed to its validation and to the diagnosis of the model. The first case consists of checking that the coefficients are statistically significant. The second is to check four assumptions: linearity, homocedasticity, normality and independence.
References
- Solanas A, Guàrdia J. Modelos de regresión lineal. En: Peró M, Leiva D, Guàrdia J, Solanas A, eds. Estadística aplicada a las ciencias sociales mediante R y R-Commander. Ibergarceta Publicaciones SL. Madrid; 2012:434-97.
- Sánchez-Villegas A, Martín-Calvo N, Martínez-González MA. Correlación y regresión lineal simple. En: Martínez González MA, Sánchez-Villegas A, Toledo Atucha EA, Faulin Fajardo J, eds. Bioestadística amigable, 3ª ed. Elsevier España SL. Barcelona; 2014: 269-326.
- Correlation and simple lineal regression. En: Logan M. Biostatistical design and análisis using R: a practical guide. Blackwell Publishing. 2010: 167-207.
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