We show how multinomial logistic models with correlated responses can be estimated within SAS software. To achieve this, random effects and marginal models are introduced and the respective SAS code is given. An example data set on physicians' recommendations and preferences in traumatic brain injury rehabilitation is used for illustration. The main motivation for this work are two recent paper...

The sociological research literature on intergenerational educational attainment has highlighted three types of theoretical frameworks in explaining to what extent social origins influences people’s educational choices and possibilities. The three explanatory frameworks are 1) the socio-economic situation in the upbringing, 2) the “cultural capital” of the home (e.g. the level of education of t...

W develop a consumer response model to evaluate and plan pricing and promotions in durable-good markets. We discuss its implementation in the U.S. automotive industry, which “spends” about $45 billion each year in price promotions. The approach is based on a random effects multinomial nested logit model of product (e.g., a vehicle model, such as Hyundai Tucson), and transaction-type choice. Tra...

Frequent and intense anthropogenic fires present meaningful challenges to forest management in the boreal forest of China. Understanding the underlying drivers of human-caused fire occurrence is crucial for making effective and scientifically-based forest fire management plans. In this study, we applied logistic regression (LR) and Random Forests (RF) to identify important biophysical and anthr...

Abstract. Data-preparation and fitting for a comprehensive model of statewise household response to the 1990 census is described, using a methodology of successive logistic regressions for longitudinally defined response variables, including indicators of response by mail, and enumerator checkin within quantile intervals of enumerator operational time for the ARA containing the household. The e...

We propose a two component graphical chain model, the discrete regression distribution, in which a set of categorical (or discrete) random variables is modeled as a response to a set of categorical and continuous covariates. We examine necessary and sufficient conditions for a discrete regression distribution to be described by a given graph. The discrete regression formulation is extended to a...

background: breast cancer is the most common cancer after lung cancer and the second cause of death. in this study we compared weibull and lognormal cure models with cox regression on the survival of breast cancer. study design: a cohort study. methods: the current study retrospective cohort study was conducted on 140 patients referred to ali ibn abitaleb hospital, rafsanjan southeastern iran f...

background: we designed an algorithmic model based on the logistic regression analysis and a non-algorithmic model based on the artificial neural network (ann). materials and methods: the ability of these models was compared together in clinical application to differentiate malignant from benign breast tumors in a study group of 161 patients' records. each patient’s record consisted of 6 s...

Two-component Poisson mixture regression is typically used to model heterogeneous count outcomes that arise from two underlying sub-populations. Furthermore, a random component can be incorporated into the linear predictor to account for the clustering data structure. However, when including random effects in both components of the mixture model, the two random effects are often assumed to be i...