Methods Using a dataset of 410 JIA patients treated with MTX, (provided by PRINTO) 3 sets of logistic regression analyses were conducted, one at each classification level, to determine the likelihood of a classification of improvement. For each level a series of univariate logistic analyses were conducted to identify, from the six COV, individually significant (p < 0.05) predictors of improveme...

Least Angle Regression is a promising technique for variable selection applications, offering a nice alternative to stepwise regression. It provides an explanation for the similar behavior of LASSO (l1-penalized regression) and forward stagewise regression, and provides a fast implementation of both. The idea has caught on rapidly, and sparked a great deal of research interest. In this paper, w...

This study focused on how an action determines impressions of the individuals participating in the action, a substantive area with problematic data in the form of constricted variances, multicollinearity, and excessive influence of a few extreme cases. Stepwise regression often is used to determine which variables influence an outcome, but can lead to mis-specifications with problematic data. T...

this study is concerned with understanding the impact of demographic changes, socioeconomic inequalities, and the availability of health factors on life expectancy (le) in the low and lower middle income countries.the cross-country data were collected from 91 countries from the united nations agencies in 2012. le is the response variable with demographics (total fertility rate, and adolescent f...

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Logistic regression studies often have several covariates and asked to cull these covariates to arrive at a parsimonious model. The goal is to maximize predictive power while minimizing the number of covariates in the model. Purposeful selection of covariates does not provide efficient model in case of large number of covariates while mechanical stepwise and best subsets selection procedures st...

In the current study two methods are evaluated for predicting the compressive strength of concrete containing metakaolin. Adaptive neuro-fuzzy inference system (ANFIS) model and stepwise regression (SR) model are developed as a reliable modeling method for simulating and predicting the compressive strength of concrete containing metakaolin at the different ages. The required data in training an...

Statistical inference based on stepwise model selection is applied regularly in ecological, evolutionary, and behavioral research. In addition to fundamental shortcomings with regard to finding the "best" model, stepwise procedures are known to suffer from a multiple-testing problem, yet the method is still widely used. As an illustration of this problem, we present results of a simulation stud...