Variable selection for predictive modeling has traditionally relied on theory in the psychological domain. Given the recent advancements in computing technology and availability, researchers are able to utilize more sophisticated mathematical modeling techniques with greater ease. The challenge becomes evaluating whether theory or mathematics should be relied upon for model development. The presented analyses compared the use of hierarchical and stepwise variable selection methods during a predictive modeling task using linear regression. The results show that the stepwise variable selection method is able to obtain a more efficient model than the hierarchical variable selection method. Implications and recommendations for researchers are f...
How can we best understand and analyze data obtained from psychological experiments? Throughout this...
Objectives: Identifying an appropriate set of predictors for the outcome of interest is a major chal...
The problem of determining the best subset has two important aspects: the choice of a criteria defin...
Explanations of human behavior are most often presented in a verbal form as theories. Psychologists ...
Simulation was used to evaluate the performances of several methods of variable selection in regress...
In this paper, we investigate on 39 Variable Selection procedures to give an overview of the existin...
Model selection is a complicated matter in science, and psychology is no exception. In particular, t...
In decision making research, scientists collect a large number of variables that may be useful in de...
The selection of a descriptor, X, is crucial for improving the interpretation and prediction accurac...
In this paper, we compare the method of Gunter et al. (2011) for variable selection in treatment com...
In this paper, we compare the method of Gunter et al. (2011) for variable selection in treatment com...
In the era of big data, analysts usually explore various statistical models or machine-learning meth...
Abstract. This paper discusses variable selection for medical decision making; in particular decisio...
Analysis of data sets that involve large numbers of variables usually entails some type of model fit...
A model is usually only an approximation of underlying reality. To access this reality in an adequat...
How can we best understand and analyze data obtained from psychological experiments? Throughout this...
Objectives: Identifying an appropriate set of predictors for the outcome of interest is a major chal...
The problem of determining the best subset has two important aspects: the choice of a criteria defin...
Explanations of human behavior are most often presented in a verbal form as theories. Psychologists ...
Simulation was used to evaluate the performances of several methods of variable selection in regress...
In this paper, we investigate on 39 Variable Selection procedures to give an overview of the existin...
Model selection is a complicated matter in science, and psychology is no exception. In particular, t...
In decision making research, scientists collect a large number of variables that may be useful in de...
The selection of a descriptor, X, is crucial for improving the interpretation and prediction accurac...
In this paper, we compare the method of Gunter et al. (2011) for variable selection in treatment com...
In this paper, we compare the method of Gunter et al. (2011) for variable selection in treatment com...
In the era of big data, analysts usually explore various statistical models or machine-learning meth...
Abstract. This paper discusses variable selection for medical decision making; in particular decisio...
Analysis of data sets that involve large numbers of variables usually entails some type of model fit...
A model is usually only an approximation of underlying reality. To access this reality in an adequat...
How can we best understand and analyze data obtained from psychological experiments? Throughout this...
Objectives: Identifying an appropriate set of predictors for the outcome of interest is a major chal...
The problem of determining the best subset has two important aspects: the choice of a criteria defin...