eComment. The importance of choosing a proper predictor variable selection method in logistic regression analyses
نویسندگان
چکیده
منابع مشابه
Variable Selection for Multivariate Logistic Regression Models
In this paper, we use multivariate logistic regression models to incorporate correlation among binary response data. Our objective is to develop a variable subset selection procedure to identify important covariates in predicting correlated binary responses using a Bayesian approach. In order to incorporate available prior information, we propose a class of informative prior distributions on th...
متن کاملVariable Selection in Logistic Regression: The British English Dative Alternation
In this paper, we address the problem of selecting the ‘optimal’ variable subset in a logistic regression model for a medium-sized data set. As a case study, we take the British English dative alternation, where speakers and writers can choose between two (equally grammatical) syntactic constructions to express the same meaning. With the help of 29 explanatory variables taken from the literatur...
متن کاملA variable selection method based on Tabu search for logistic regression models
A Tabu Search method to select variables that are subsequently used in Logistic Regression Models is proposed and analysed. The aim is to find from among a set of m variables a smaller subset which enables an efficient classification of cases. Reducing dimensionality has some advantages such as reducing the costs of data acquisition, better understanding of the final classification model, and a...
متن کاملLogistic Regression: The Importance of Being Improper
Learning linear predictors with the logistic loss—both in stochastic and online settings— is a fundamental task in learning and statistics, with direct connections to classification and boosting. Existing “fast rates” for this setting exhibit exponential dependence on the predictor norm, and Hazan et al. (2014) showed that this is unfortunately unimprovable. Starting with the simple observation...
متن کاملA Novel Resampling Method for Variable Selection in Robust Regression
Variable selection in regression analysis is of vital importance for data analyst and researcher to fit the parsimonious regression model. With the inundation of large number of predictor variables and large data sets requiring analysis and empirical modeling, contamination becomes usual problem. Accordingly, robust regression estimators are designed to easily fit contaminated data sets. In the...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Interactive CardioVascular and Thoracic Surgery
سال: 2016
ISSN: 1569-9293,1569-9285
DOI: 10.1093/icvts/ivv403