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

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.

Keywords:

• Biological control
• exponentiated models
• half-normal plots with simulation envelopes
• location-scale modelling
• mixed survival models

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

RAM was funded by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Grant No. 2014/12903-8). Exchange visits between CGBD and JH were partially supported by CNPq, FAPESP and Science Foundation Ireland (SFI). WACG was funded by CNPq.