This paper derives conditions under which the standard decomposition of unconditional expected utility into marginal probabilities and conditional expected utilities generalizes to Cumulative Prospect Theory. The results are relevant for empirical analyses in which marginal probabilities are used as explanatory variables.

SUMMARY A marginal model for the analysis of binomial data involving one or two random factors is presented. Two variance-covariance models are derived based on the multiplicative error formulation. The parameters of mean and variance components are estimated using the quasi-likelihood and method of moments, respectively. An application of the model is illustrated by an analysis of multivariate...

In the paper two approaches to the problem of estimation of transition probabilities are considered. The approach by McCullagh and Nelder [5], based on the independent model and the quasi-likelihood function, is compared with the approach based on the marginal model and the standard likelihood function. The estimates following from these two approaches are illustrated on a simple example which ...

We assume ε(t) | {X(s), y(s− 1), s ≤ t} ∼ N(0,Σ). This is the assumption that X(t) is predetermined in this system. In this notation, each equation (column of the system) has the same X(t) variable on the right-hand side and a distinct coefficient vector (column of B). However, we can consider versions of the system with 0 constraints on elements of B, which create different lists of variables ...

In this tutorial we show how complete hierarchical multinomial marginal (HMM) models for categorical variables can be defined, estimated and tested using the hmmm package.

This paper extends the Bayes marginal model plot (BMMP) model assessment technique from a traditional logistic regression setting to a multilevel application in the area of criminal justice. Convicted felons in the United States receive either a prison sentence or a less severe jail or non-custodial sentence. Researchers have identified many determinants of sentencing variation across the count...

We examine bias corrections which have been proposed for the Fixed Effects Panel Probit model with exogenous regressors, using several different data generating processes to evaluate the performance of the estimators in different situations. We find a best estimator across all cases for coefficient estimates, but when the marginal effects are the quantity of interest no analytical correction is...

This paper is concerned with combined inference for point processes on the real line observed in a broken interval. For such processes, the classic history-based approach cannot be used. Instead, we adapt tools from sequential spatial point processes. For a range of models, the marginal and conditional distributions are derived. We discuss likelihood based inference as well as parameter estimat...

Zeger and Liang (1992) allege that regression parameter estimates from transition models tend to be smaller in absolute value than regression parameter estimates from marginal models. This statement is true in typical longitudinal data situations for the relation between the true parameters of the marginal and transition model. However, under the assumption of a transition model the Generalized...