We analysed data from 64 patients with Wegener's granulomatosis to determine predictor variables of outcome. The mean period of observation after the diagnosis had been established was 3.2 (range 0.1-11.2) years. At the time of diagnosis, 15 (23%) patients had only local symptoms. The disease was generalized to multiple organs in 49 (77%) patients. Renal biopsies were obtained in 33 patients; 1...

research findings suggest that the family context and communication patterns have high correlation with adolescent’s mental health indicators such as anxiety. therefore, the current study aimed to investigate the mediator role of coping strategies in relation between family communication patterns and students social anxiety. 140 students of shiraz guidance schools were studied they completed th...

This article reports on the results of a multiple regression analysis of an adolescent multiple drug use index on 17 predictor variables from the PRIDE CANADA Drug survey with 18,685 Grades 9 through 12 students in two Western Canadian provinces in 1995-96. The predictor variables represent eight familial, five school and peer, and four individual level attributes and behaviours. The regression...

Redundancy analysis (RA) is a versatile technique used to predict multivariate criterion variables from multivariate predictor variables. The reduced-rank feature of RA captures redundant information in the criterion variables in a most parsimonious way. A ridge type of regularization was introduced in RA to deal with the multicollinearity problem among the predictor variables. The regularized ...

Partial Least Squares Regression (PLSR) is a method for constructing predictive models when the variables are many and highly collinear. Its goal is to predict a set of response variables from a set of predictor variables. This prediction is achieved by extracting a set of orthogonal factors called latent variables from the predictor variables. This study investigated the performances of model ...

This paper deals with a nonlinear errors-in-variables model where the distributions of the unobserved predictor variables and of the measurement errors are nonparametric. Using the instrumental variable approach, we propose method of moments estimators for the unknown parameters and simulation-based estimators to overcome the possible computational difficulty of minimizing an objective function...

Raymond J. Carroll Department of Statistics Texas A&M University College Station, TX 77843 We study logistic regression with response y when the true predictor x is measured with· error and the observable data consist of pairs (y,w), where w is correlated with x. Two approaches to estimation are studied. In the first, integrated likelihood estimates are obtained from the conditional distributio...