Modeling Insect-Egg Data with Excess Zeros using Zero-Inflated Regression Models

Abstract

As zero-inflated observations occur very often in studies on plant protection, models taking into account zero-inflated observations are frequently required. Especially, zero-inflated observations occur in large numbers for insects whose post-oviposition period lasts long, or that generally lay their eggs during the first days of the oviposition period. For the data used in this study, 1114 (43.84%) of the 2541 observations were zero. In the selection of an appropriate regression model, zeroinflated negative binomial regression was chosen as the best model. Inall regression models, the day of laying and the three different hosts were seen to have a significant effect on daily egg numbers (p < 0.01).