Juggling Between Parental and School Expectations: The Development of Domain‐Specific Acculturation Orientations in Early Adolescence

We examined how perceived acculturation expectations from parents and school, and ethnic discrimination predicted early adolescents’ heritage and mainstream acculturation orientations at home (private domain) and in school (public domain) one year later. We surveyed 263 early adolescents of immigrant background in Germany (M_age = 10.44 years, 60% female). Multigroup path analyses revealed that perceived acculturation expectations and ethnic discrimination were more strongly related to adolescents’ private than public acculturation orientations. Parental heritage expectations were the strongest predictor of adolescents’ acculturation orientations. Boys were more susceptible than girls to ethnic discrimination and acculturation expectations in school, which affected their private and public acculturation orientations. Results highlight the importance of integrating domain‐specific and gendered experiences when analyzing adolescents’ acculturative development.     

Drivers of fish assemblage structures in a Neotropical urban watershed

Urban Ecosystems - Urbanization results in major changes in stream morphology, hydrology, and water quality; the consequences on fish assemblage of Neotropical urban streams remain poorly...     

Accurate estimation for extra-Poisson variability assuming random effect models

In this study, the components of extra-Poisson variability are estimated assuming random effect models under a Bayesian approach. A standard existing methodology to estimate extra-Poisson variability assumes a negative binomial distribution. The obtained results show that using the proposed random effect model it is possible to get more accurate estimates for the extra-Poisson variability components when compared to the use of a negative binomial distribution where it is possible to estimate only one component of extra-Poisson variability. Some illustrative examples are introduced considering real data sets.     

A new regression model for bimodal data and applications in agriculture

We define the odd log-logistic exponential Gaussian regression with two systematic components, which extends the heteroscedastic Gaussian regression and it is suitable for bimodal data quite common in the agriculture area. We estimate the parameters by the method of maximum likelihood. Some simulations indicate that the maximum-likelihood estimators are accurate. The model assumptions are checked through case deletion and quantile residuals. The usefulness of the new regression model is illustrated by means of three real data sets in different areas of agriculture, where the data present bimodality.