The belonging model of trust

Although we know that high‐quality employee–organization relationships are beneficial, these relationships are complex and not fully understood, especially among employees of nonprofit organizations. In particular, we know little about how these employees perceive trust, which may overlook an important contributor to effective management. We begin to address this issue by testing a new theoretical model that conceptualizes perceived insider status, psychological ownership, and organizational identification as foundations for the perception of justice and subsequent trust. Our results indicate that psychological ownership and perceived insider status relate to trust through procedural and interpersonal justice. These results contrast those typically found in for‐profit contexts in that organizational identification did not predict justice and that distributive and informational justice did not predict trust.     

Total testosterone levels are correlated to metabolic syndrome components

Introduction: Metabolic syndrome (MetS) is a constellation of interrelated risk factors of metabolic origin. Some studies suggest a possible link between low total testosterone (TT) levels and the presence of MetS.

Aim: To analyze the strength and independence of associations between TT and MetS components in non-diabetic men.

Methods: In this cross-sectional study, 143 non-diabetic men older than 40 were analyzed.

Main outcomes measure: Blood samples were collected to evaluate metabolic profile and TT levels. MetS was defined as the presence of three or more of the following characteristics: fasting blood glucose levels?≥?100?mg/dL, triglyceride?≥?150?mg/dL, HDL-c??102?cm.

Results: Mean age of the study population was 61.5?±?8.61 years old. MetS was present in 47.9% of the individuals. Thirty-four men had low TT and MetS was observed in 23 (70%) against 50 (46%) in those with normal TT (≥?300?ng/dL) (OR 4.94, p?p?=?0.03) and HDL-c (Beta: 0.19; p?=?0.04) remained significantly correlated with TT levels.

Conclusions: Low TT levels were associated with MetS diagnosis. Abdominal obesity was the MetS component independently correlated to low TT levels.     

Influence diagnostics in a multivariate normal regression model with general parameterization

Patriota and Lemonte [24] introduced a quite general multivariate normal regression model. This model considers that the mean vector and the covariance matrix share the same vector of parameters. In this paper we present some influence assessment for this model, such as the local influence, total local influence of an individual and generalized leverage which are discussed. Additionally, the normal curvatures for local influence studies are derived under some perturbation schemes.     

The Poisson Generalized Linear Failure Rate Model

We formulate a new cure rate survival model by assuming that the number of competing causes of the event of interest has the Poisson distribution, and the time to this event has the generalized linear failure rate distribution. A new distribution to analyze lifetime data is defined from the proposed cure rate model, and its quantile function as well as a general expansion for the moments is derived. We estimate the parameters of the model with cure rate in the presence of covariates for censored observations using maximum likelihood and derive the observed information matrix. We obtain the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and present some ways to perform global influence analysis. The usefulness of the proposed cure rate survival model is illustrated in an application to real data.     

Signed likelihood ratio tests in the Birnbaum-Saunders regression model

The Birnbaum-Saunders regression model is becoming increasingly popular in lifetime analyses and reliability studies. In this model, the signed likelihood ratio statistic provides the basis for testing inference and construction of confidence limits for a single parameter of interest. We focus on the small sample case, where the standard normal distribution gives a poor approximation to the true distribution of the statistic. We derive three adjusted signed likelihood ratio statistics that lead to very accurate inference even for very small samples. Two empirical applications are presented.     

Multivariate elliptical models with general parameterization

In this paper we introduce a general elliptical multivariate regression model in which the mean vector and the scale matrix have parameters (or/and covariates) in common. This approach unifies several important elliptical models, such as nonlinear regressions, mixed-effects model with nonlinear fixed effects, errors-in-variables models, and so forth. We discuss maximum likelihood estimation of the model parameters and obtain the information matrix, both observed and expected. Additionally, we derived the generalized leverage as well as the normal curvatures of local influence under some perturbation schemes. An empirical application is presented for illustrative purposes.     

Non Null Asymptotic Distributions of Some Criteria in Censored Exponential Regression

In this article, we consider the class of censored exponential regression models which is very useful for modeling lifetime data. Under a sequence of Pitman alternatives, the asymptotic expansions up to order n^{? 1/2} of the non null distribution functions of the likelihood ratio, Wald, Rao score, and gradient statistics are derive in this class of models. The non null asymptotic distribution functions of these statistics are obtained for testing a composite null hypothesis in the presence of nuisance parameters. The power of all four tests, which are equivalent to first order, are compared based on these non null asymptotic expansions. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, we consider Monte Carlo simulations. We also present an empirical application for illustrative purposes.     

Local power properties of some asymptotic tests in symmetric linear regression models

In this paper we obtain asymptotic expansions, up to order n^−1/2 and under a sequence of Pitman alternatives, for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the class of symmetric linear regression models. This is a wide class of models which encompasses the t model and several other symmetric distributions with longer-than normal tails. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, Monte Carlo simulations are presented. An empirical application to a real data set is considered for illustrative purposes.     

Small-Sample Corrections for Score Tests in Birnbaum–Saunders Regressions

In this article, we deal with the issue of performing accurate small-sample inference in the Birnbaum–Saunders regression model, which can be useful for modeling lifetime or reliability data. We derive a Bartlett-type correction for the score test and numerically compare the corrected test with the usual score test and some other competitors.