Location-scale mixed models and goodness-of-fit assessment applied to insect ecology

R. A. Moral, J. Hinde, E. M. M. Ortega, C. G. B. Demétrio and W. A. C. Godoy

Journal of Applied Statistics, 2020, vol. 47, issue 10, 1776-1793

Abstract: Survival models have been extensively used to analyse time-until-event data. There is a range of extended models that incorporate different aspects, such as overdispersion/frailty, mixtures, and flexible response functions through semi-parametric models. In this work, we show how a useful tool to assess goodness-of-fit, the half-normal plot of residuals with a simulated envelope, implemented in the hnp package in R, can be used on a location-scale modelling context. We fitted a range of survival models to time-until-event data, where the event was an insect predator attacking a larva in a biological control experiment. We started with the Weibull model and then fitted the exponentiated-Weibull location-scale model with regressors both for the location and scale parameters. We performed variable selection for each model and, by producing half-normal plots with simulated envelopes for the deviance residuals of the model fits, we found that the exponentiated-Weibull fitted the data better. We then included a random effect in the exponentiated-Weibull model to accommodate correlated observations. Finally, we discuss possible implications of the results found in the case study.

Date: 2020
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DOI: 10.1080/02664763.2019.1693522

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