Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/43191
Title: The Probability of Improved Prediction: a new concept in statistical inference
Authors: THAS, Olivier 
JASPERS, Stijn 
Issue Date: 2024
Source: 
Abstract: In an attempt to provide an answer to the increasing criticism against p-values and to bridge the gap between statistical inference and prediction modelling, we introduce the probability of improved prediction (PIP). In general, the PIP is a probabilistic measure for comparing two competing models. Three versions of the PIP and several estimators are introduced and the relationships between them, p-values and the mean squared error are investigated. The performance of the estimators is assessed in a simulation study. An application shows how the PIP can support p-values to strengthen the conclusions or possibly point at issues with e.g. replicability.
Keywords: Cross-validation;Hypothesis testing;Model comparison;Prediction modelling;Sample splitting
Document URI: http://hdl.handle.net/1942/43191
Rights: CC BY-NC-ND 4.0
Category: A2
Type: Preprint
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
2405.17064v1.pdf4.23 MBAdobe PDFView/Open
Show full item record

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.