Some restriction tests in a new class of regression models for proportions

The main purpose of this work is to study the behaviour of Skovgaard`s [Skovgaard, I.M., 2001. Likelihood asymptotics. Scandinavian journal of Statistics 28, 3-32] adjusted likelihood ratio statistic in testing simple hypothesis in a new class of regression models proposed here. The proposed class of regression models considers Dirichlet distributed observations, and the parameters that index the Dirichlet distributions are related to covariates and unknown regression coefficients. This class is useful for modelling data consisting of multivariate positive observations summing to one and generalizes the beta regression model described in Vasconcellos and Cribari-Neto [Vasconcellos, K.L.P., Cribari-Neto, F., 2005. Improved maximum likelihood estimation in a new class of beta regression models. Brazilian journal of Probability and Statistics 19,13-31]. We show that, for our model, Skovgaard`s adjusted likelihood ratio statistics have a simple compact form that can be easily implemented in standard statistical software. The adjusted statistic is approximately chi-squared distributed with a high degree of accuracy. Some numerical simulations show that the modified test is more reliable in finite samples than the usual likelihood ratio procedure. An empirical application is also presented and discussed. (C) 2009 Elsevier B.V. All rights reserved.

The complementary exponential power lifetime model

In this paper we propose a new lifetime distribution which can handle bathtub-shaped unimodal increasing and decreasing hazard rate functions The model has three parameters and generalizes the exponential power distribution proposed by Smith and Bain (1975) with the inclusion of an additional shape parameter The maximum likelihood estimation procedure is discussed A small-scale simulation study examines the performance of the likelihood ratio statistics under small and moderate sized samples Three real datasets Illustrate the methodology (C) 2010 Elsevier B V All rights reserved

Transformed generalized linear models

The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the rth moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin er al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214-223]. The usefulness of these models is illustrated in a Simulation study and in applications to three real data sets. (C) 2009 Elsevier B.V. All rights reserved.

Power series generalized nonlinear models

We introduce in this paper a new class of discrete generalized nonlinear models to extend the binomial, Poisson and negative binomial models to cope with count data. This class of models includes some important models such as log-nonlinear models, logit, probit and negative binomial nonlinear models, generalized Poisson and generalized negative binomial regression models, among other models, which enables the fitting of a wide range of models to count data. We derive an iterative process for fitting these models by maximum likelihood and discuss inference on the parameters. The usefulness of the new class of models is illustrated with an application to a real data set. (C) 2008 Elsevier B.V. All rights reserved.

Missing data mechanisms and their implications on the analysis of categorical data

We review some issues related to the implications of different missing data mechanisms on statistical inference for contingency tables and consider simulation studies to compare the results obtained under such models to those where the units with missing data are disregarded. We confirm that although, in general, analyses under the correct missing at random and missing completely at random models are more efficient even for small sample sizes, there are exceptions where they may not improve the results obtained by ignoring the partially classified data. We show that under the missing not at random (MNAR) model, estimates on the boundary of the parameter space as well as lack of identifiability of the parameters of saturated models may be associated with undesirable asymptotic properties of maximum likelihood estimators and likelihood ratio tests; even in standard cases the bias of the estimators may be low only for very large samples. We also show that the probability of a boundary solution obtained under the correct MNAR model may be large even for large samples and that, consequently, we may not always conclude that a MNAR model is misspecified because the estimate is on the boundary of the parameter space.

Inference for a skew extension of the Grubbs model

In this paper, we discuss inferential aspects for the Grubbs model when the unknown quantity x (latent response) follows a skew-normal distribution, extending early results given in Arellano-Valle et al. (J Multivar Anal 96:265-281, 2005b). Maximum likelihood parameter estimates are computed via the EM-algorithm. Wald and likelihood ratio type statistics are used for hypothesis testing and we explain the apparent failure of the Wald statistics in detecting skewness via the profile likelihood function. The results and methods developed in this paper are illustrated with a numerical example.

First molecular estimate of sex-ratio of southern right whale calves, Eubalaena australis, for Brazilian waters

The southern right whale (Eubalaena australis) was one of the most intensively hunted whales between the 17th and 20th centuries in the southern hemisphere. Recent estimates indicate that today there are around 7000 whales, representing 5 to 10% Of its original population. On the other hand, recent studies estimated that the population that migrates to the Brazilian coast grew by 14% from 1987 to 2003. However, there is no information about sex-ratio for adults or for calves in this region, which is an important parameter for understanding the biology of the species. We present here the first estimate Of calves` sex-ratio of southern right whales found along the southern Brazilian coast, one of the most important wintering grounds for the species. Sex was molecularly indentified for 21 biopsies collected from calves between 1998 and 2002, along the coast of Rio Grande do Sul and Santa Catarina States, in southern Brazil. The sex-ratio was two females for one male, however, it was not statistically different (chi(2) test, alpha = 0.05; df = 1) from the expected ratio of 1:1. This result is in accordance with the sex-ratio estimated for the species of all ages using external morphology (and behaviour in formation), (is well as for most species of baleen whales.

Determination of the susceptibility of Rhipicephalus (Boophilus) microplus (Acari: Ixodidae) to ivermectin and fipronil by Larval Immersion Test (LIT) in Uruguay

Rhipicephalus (Boophilus) microplus is an important cattle pest in Uruguay, and the law regulates its control. It is resistant to organophosphates, synthetic pyrethroids and, as recently discovered, to fipronil. Resistance to macrocyclic lactones (MLs) and amitraz have not been documented; however, veterinarians and farmers have reported treatment failures. The objective of the present work was to study the susceptibility of cattle tick strains from different Uruguayan counties to ivermectin (IVM) and fipronil by using the Larval Immersion Test (LIT). The Mozo strain was used as the susceptible reference strain. From 2007 to 2009, twenty-eight tick populations were collected from different cattle farms with and without history of IVM or fipronil use. A probit analysis estimated dose-mortality regressions, lethal concentrations (LC), and confidence intervals. The resistance ratio (RR) was determined at the LC(50) and LC(90) estimates. To classify a tick population in relation to resistance, three categories based on a statistical analysis of LC and RR between field populations and Mozo strains were defined: susceptible (no differences), incipient resistance (differences and RR(50) < 2) and resistant (differences and RR(50) >= 2). Eighteen field populations were tested with IVM and five of them presented a RR(50) range between 1.35 and 1.98 and the LC(50/90), which is statistically different from the Mozo strain (incipient resistance). However, the RR(90) increases >= 2 in four of the populations, confirming that tick resistance to IVM is emergent. The low RR values obtained could be a result of a low frequency of treatments with IVM. Twenty-seven tick populations were tested with fipronil and six were diagnosed as resistant according to the LIT. Cross-resistance was not observed between fipronil and IVM on these tick populations. The current study presents different R. (B.) microplus populations with an incipient resistance to IVM, and indicates that the fipronil tick resistance is restricted to certain areas in Uruguay. (c) 2011 Elsevier B.V. All rights reserved.