Non-Gaussian outcomes are often modeled using members of the so-called exponential family. Notorious members are the Bernoulli model for binary data, leading to logistic regression, and the Poisson model for count data, leading to Poisson regression. Two of the main reasons for extending this family are (1) the occurrence of overdispersion, meaning that the variability in the data is not adequately described by the models, which often exhibit a prescribed mean–variance link, and (2) the accommodation of hierarchical structure in the data, stemming from clustering in the data which, in turn, may result from repeatedly measuring the outcome, for various members of the same family, etc. The first issue is dealt with through a variety of overdispersion models, such as, for example, the beta-binomial model for grouped binary data and the negative-binomial model for counts. Clustering is often accommodated through the inclusion of random subject-specific effects. Though not always, one conventionally assumes such random effects to be normally distributed. While both of these phenomena may occur simultaneously, models combining them are uncommon. This paper proposes a broad class of generalized linear models accommodating overdispersion and clustering through two separate sets of random effects. We place particular emphasis on so-called conjugate random effects at the level of the mean for the first aspect and normal random effects embedded within the linear predictor for the second aspect, even though our family is more general. The binary, count and time-to-event cases are given particular emphasis. Apart from model formulation, we present an overview of estimation methods, and then settle for maximum likelihood estimation with analytic–numerical integration. Implications for the derivation of marginal correlations functions are discussed. The methodology is applied to data from a study in epileptic seizures, a clinical trial in toenail infection named onychomycosis and survival data in children with asthma.

Biological control of pests is an important branch of entomology, providing environmentally friendly forms of crop protection. Bioassays are used to find the optimal conditions for the production of parasites and strategies for application in the field. In some of these assays, proportions are measured and, often, these data have an inflated number of zeros. In this work, six models will be applied to data sets obtained from biological control assays for Diatraea saccharalis , a common pest in sugar cane production. A natural choice for modelling proportion data is the binomial model. The second model will be an overdispersed version of the binomial model, estimated by a quasi-likelihood method. This model was initially built to model overdispersion generated by individual variability in the probability of success. When interest is only in the positive proportion data, a model can be based on the truncated binomial distribution and in its overdispersed version. The last two models include the zero proportions and are based on a finite mixture model with the binomial distribution or its overdispersed version for the positive data. Here, we will present the models, discuss their estimation and compare the results.

The preslaughter handling and transport of broilers are stressful operations that might affect welfare and meat quality and could increase numbers of deaths before slaughter. However, the influence of thermal factors during transportation and lairage at slaughterhouses is complex in subtropical regions, where increasing temperature and high RH are the major concerns regarding animal survival before slaughter. In this study we assessed the influence of a controlled lairage environment on preslaughter mortality rates of broiler chickens that were transported during different seasons of the year and had varying lairage times in the subtropical climate. Preslaughter data from 13,937 broiler flocks were recorded daily during 2006 in a commercial slaughterhouse in southeastern Brazil. The main factors that influenced daily mortality rate were mean dry bulb temperature and RH, lairage time, daily periods, density of broilers per crate, season of the year, stocking density per lorry, transport time, and distance between farms and slaughterhouse. A holding area at the slaughterhouse with environmental control was assessed. Using a double GLM for mean and dispersion modeling, the seasons were found to have significant effects (P < 0.05) on average mortality rates. The highest incidence was observed in summer (0.42%), followed by spring (0.39%), winter (0.28%), and autumn (0.23%). A decrease of preslaughter mortality of broilers during summer (P < 0.05) was observed when the lairage time was increased, mainly after 1 h of exposure to a controlled environment. Thus, lairage for 3 to 4 h in a controlled lairage environment during the summer and spring is necessary to reduce the thermal load of broiler chickens.

The objective of this work was to determine the potential of five species of Scelionidae wasps - Telenomus podisi, Trissolcus basalis, Trissolcus urichi, Trissolcus teretis and Trissolcus brochymenae - as natural enemies of the neotropical stink bug Dichelops melacanthus, and to determine if the presence of eggs of other stink bug species influences the parasitism and development of the parasitoids. Two kinds of experiments were done in laboratory: without choice of hosts (eggs of D. melacanthus) and with choice (eggs of D. melacanthus and of Euschistus heros). Biological parameters, including proportion of parasitism, immature survivorship, progeny sex ratio, immature stage development period, and host preference were recorded. All the evaluated parasitoids can parasitize and develop on D. melacanthus eggs. The first choice of eggs did not influence the proportion of D. melacanthus eggs parasitized by Tr. basalis, Tr. teretis or Tr. brochymenae. However, D. melacanthus eggs as the first choice of Te. podisi and Tr. urichi increased, respectively, 9 and 14 times the chance for parasitism on eggs of this species. Behavioral and ecological aspects of parasitoids should be considered prior to their use in biological control programs.

This work aimed to assess the effects of preslaughter lairage time on the welfare and mortality of broilers transported in different farm-abattoir distances. It was evaluated 215 poultry transport trucks from a commercial poultry slaughterhouse from 2006 to 2007. Data were obtained from the holding area acclimatized through fans and water misting in the mornings, afternoons and at night. The thermal variables (temperature and relative humidity), distance, lairage time and density of birds per cage were considered in the analysis. The effects of distance and lairage time were important in the variation of rectal temperature of the animals and on the number of dead animals per truck. Two models were developed (mean and dispersion), for each response variable in function of the interaction between lairage time and distance. As the lairage time in the holding area increased, the rectal temperature of the birds was reduced for all the studied distances. In farm-abattoir distances higher than 25 km, mortality was low when lairage time was lower than 1 hour. However, for distances below 25 km, in the same time interval, the number of dead birds was two-fold higher than in the first situation. The adjustment of lairage time has to be done accordingly to the distance provided that the lairage environment is correctly climatized.