Quantitative trait loci (QTL) mapping is a growing field in statistical genetics. In plants, QTL detection experiments often feature replicates or clones within a specific genetic line. In this work, a Bayesian hierarchical regression model is applied to simulated QTL data and to a dataset from...

The authors study alternative estimators of the impacts of higher level variables in multilevel models. This is important since many of the important variables in social science research are higher level factors having impacts on many lower level outcomes such as school achievement and...

We propose a class of Bayesian semiparametric mixed-effects models; its distinctive feature is the randomness of the grouping of observations, which can be inferred from the data. The model can be viewed under a more natural perspective, as a Bayesian semiparametric regression model on the...

This study develops two-level hierarchical model that identifies factors that favor or hamper the use of Internet in Africa. We used data from a survey covering 17 African countries. Our results confirm that urbanization and the spread of Internet infrastructures play an important role in...

The literature is unclear about how firm and country effects influence performance over time. Under the initial hypotheses that there are significant changes in the performance of companies operating in Brazil in recent years and that these variations are due to existing characteristics in each...

The multivariate linear mixed model (MLMM) has become the most widely used tool for analyzing multi-outcome longitudinal data. Although it offers great flexibility for modeling the between- and within-subject correlation among multi-outcome repeated measures, the underlying normality assumption...

The generalized linear mixed models (GLMMs) for clustered data are studied when covariates are measured with error. The most conventional measurement error models are based on either linear mixed models (LMMs) or GLMMs. Even without the measurement error, the frequentist analysis of LMM, and...

The theory of human capital is one way to explain individual decisions to produce scientific research. However, this theory, even if it reckons the importance of time in science, is too short for explaining the existing diversity of scientific output. The present paper introduces the social...

Models of decision-making in multi-level, hierarchical systems in the literature have been restricted to structures where the system is strictly pyramidal in nature. We will show that this restriction has been self-imposed and that existing models can be modified to represent a wide range of...

Expert panels are playing an increasingly important role in U.S. health policy decision making. A fundamental issue in these applications is how to synthesize the judgments of individual experts into a group judgment. In this paper we propose an approach to synthesis based on Bayesian...