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Diagnostic plots in beta-regression models

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  • Li-Chu Chien

Abstract

Two diagnostic plots for selecting explanatory variables are introduced to assess the accuracy of a generalized beta-linear model. The added variable plot is developed to examine the need for adding a new explanatory variable to the model. The constructed variable plot is developed to identify the nonlinearity of the explanatory variable in the model. The two diagnostic procedures are also useful for detecting unusual observations that may affect the regression much. Simulation studies and analysis of two practical examples are conducted to illustrate the performances of the proposed plots.

Suggested Citation

  • Li-Chu Chien, 2011. "Diagnostic plots in beta-regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(8), pages 1607-1622, July.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:8:p:1607-1622
    DOI: 10.1080/02664763.2010.515677
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    References listed on IDEAS

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    1. P. Wang, 1991. "Diagnostics and score statistics in regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(4), pages 647-656, December.
    2. Patricia Espinheira & Silvia Ferrari & Francisco Cribari-Neto, 2008. "On beta regression residuals," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(4), pages 407-419.
    3. Espinheira, Patri­cia L. & Ferrari, Silvia L.P. & Cribari-Neto, Francisco, 2008. "Influence diagnostics in beta regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4417-4431, May.
    4. Silvia Ferrari & Francisco Cribari-Neto, 2004. "Beta Regression for Modelling Rates and Proportions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(7), pages 799-815.
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