The use of in Model Selection is a common practice in econometrics. The rationale is that the statistic produces a consistent estimator of the true coefficient of determination for the underlying data while taking into consideration the number of variables involved in the model. This pursuit of parsimony comes with a cost: The researcher has no control over the error probabilities of the statistic. Alternative measures of goodness of fit, such as the Schwarz Information Criterion, provide only a marginal improvement to the problem. The F-Test under the Neyman-Pearson testing framework will provide the best alternative for model selection criteria
Model selection is a complicated matter in science, and psychology is no exception. In particular, t...
Model Selection is a key part of many ecological studies, with Akaike’s Information Criterion (AIC) ...
This paper investigates four topics. (1) It examines the different roles played by the propensity sc...
The use of R-squared in Model Selection is a common practice in econometrics. The rationale is that ...
The problem of statistical model selection in econometrics and statistics is reviewed. Model selecti...
This paper outlines several difficulties with testing economic theories, particularly that the theor...
Model selection criteria are used in many contexts in economics. The issue of determining an approp...
We outline a range of criteria for evaluating model selection approaches that have been used in the ...
Variable selection methods and model selection approaches are valuable statistical tools, which are ...
performance. (2) Model selection does not require the specification of a correct model for its valid...
Model selection methods provide a way to select one model among a set of models in a statistically v...
<p>Competing models arise naturally in many research fields, such as survival analysis and economics...
In the era of big data, analysts usually explore various statistical models or machine-learning meth...
Simulation was used to evaluate the performances of several methods of variable selection in regress...
Model selection is often conducted by ranking models by their out-of-sample forecast error. Such cri...
Model selection is a complicated matter in science, and psychology is no exception. In particular, t...
Model Selection is a key part of many ecological studies, with Akaike’s Information Criterion (AIC) ...
This paper investigates four topics. (1) It examines the different roles played by the propensity sc...
The use of R-squared in Model Selection is a common practice in econometrics. The rationale is that ...
The problem of statistical model selection in econometrics and statistics is reviewed. Model selecti...
This paper outlines several difficulties with testing economic theories, particularly that the theor...
Model selection criteria are used in many contexts in economics. The issue of determining an approp...
We outline a range of criteria for evaluating model selection approaches that have been used in the ...
Variable selection methods and model selection approaches are valuable statistical tools, which are ...
performance. (2) Model selection does not require the specification of a correct model for its valid...
Model selection methods provide a way to select one model among a set of models in a statistically v...
<p>Competing models arise naturally in many research fields, such as survival analysis and economics...
In the era of big data, analysts usually explore various statistical models or machine-learning meth...
Simulation was used to evaluate the performances of several methods of variable selection in regress...
Model selection is often conducted by ranking models by their out-of-sample forecast error. Such cri...
Model selection is a complicated matter in science, and psychology is no exception. In particular, t...
Model Selection is a key part of many ecological studies, with Akaike’s Information Criterion (AIC) ...
This paper investigates four topics. (1) It examines the different roles played by the propensity sc...