Frequentist Post-Data Inference

The end result of an experiment is an inference, which is typically made after the data have been seen (a post-data inference). Classical frequency theory has evolved around pre-data inferences, those that can be made in the planning stages of an experiment, before data are collected. Such pre-data...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:	International Statistical Review / Revue Internationale de Statistique. - Blackwell Publishing Ltd. - 63(1995), 3, Seite 325-344
1. Verfasser:	Goutis, Constantinos (VerfasserIn)
Weitere Verfasser:	Casella, George
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	1995
Zugriff auf das übergeordnete Werk:	International Statistical Review / Revue Internationale de Statistique
Schlagworte:	Accuracy estimation Conditional confidence Conditional evaluation Confidence intervals Decision theory Hypothesis testing Loss estimation Relevant sets Sample space partitions Mathematics Behavioral sciences


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520			\|a The end result of an experiment is an inference, which is typically made after the data have been seen (a post-data inference). Classical frequency theory has evolved around pre-data inferences, those that can be made in the planning stages of an experiment, before data are collected. Such pre-data inferences are often not reasonable as post-data inferences, leaving a frequentist with no inference conditional on the observed data. We review the various methodologies that have been suggested for frequentist post-data inference, and show how recent results have given us a very reasonable methodology. We also discuss how the pre-data/post-data distinction fits in with, and subsumes, the Bayesian/frequentist distinction. /// Le résultat final d'une expérience consiste en une inférence, généralement postérieure aux observations (dite inférence post-observationnelle). La théorie fréquentiste classique s'est développée à partir d'inférences pré-observationnelles, comme celles que l'on peut faire lors de l'établissement de plans d'expérience, avant que les données soient recueillies. Les inférences pré-observationnelles ne sont généralement pas acceptables comme inférences post-observationnelles, ce qui laisse les fréquentists sans alternative inférentielle conditionnelle aux observations. Cet article rappelle les diverses approches qui ont été proposées comme inférences post-observationnelles fréquentistes et montre comment des résultats récents ont conduit à une méthodologie somme toute fort acceptable. Nous indiquons également comment la séparation pré-observationnelle/post-observationnelle se rapporte à l'opposition fréquentiste/bayésien, tout en la dépassant.
540			\|a Copyright 1995 International Statistical Institute
650		4	\|a Accuracy estimation
650		4	\|a Conditional confidence
650		4	\|a Conditional evaluation
650		4	\|a Confidence intervals
650		4	\|a Decision theory
650		4	\|a Hypothesis testing
650		4	\|a Loss estimation
650		4	\|a Relevant sets
650		4	\|a Sample space partitions
650		4	\|a Mathematics \|x Applied mathematics \|x Statistics \|x Applied statistics \|x Statistical results \|x Statistical properties \|x Estimate reliability
650		4	\|a Behavioral sciences \|x Psychology \|x Cognitive psychology \|x Cognitive processes \|x Thought processes \|x Reasoning \|x Inference
650		4	\|a Mathematics \|x Pure mathematics \|x Probability theory \|x Probability interpretations \|x Frequentism
650		4	\|a Mathematics \|x Applied mathematics \|x Statistics \|x Applied statistics \|x Inferential statistics \|x Statistical estimation \|x Estimation methods \|x Estimators
650		4	\|a Mathematics \|x Pure mathematics \|x Probability theory \|x Probabilities \|x Conditional probabilities
650		4	\|a Mathematics \|x Applied mathematics \|x Statistics \|x Applied statistics \|x Statistical results \|x Statistical properties \|x Estimate reliability \|x Confidence interval
650		4	\|a Mathematics \|x Applied mathematics \|x Statistics \|x Applied statistics \|x Inferential statistics \|x Statistical estimation \|x Estimation methods
650		4	\|a Mathematics \|x Pure mathematics \|x Probability theory \|x Probabilities
650		4	\|a Mathematics \|x Mathematical expressions \|x Mathematical functions \|x Indicator functions
650		4	\|a Mathematics \|x Mathematical values \|x Mathematical variables \|x Mathematical independent variables
655		4	\|a research-article
700	1		\|a Casella, George \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t International Statistical Review / Revue Internationale de Statistique \|d Blackwell Publishing Ltd \|g 63(1995), 3, Seite 325-344 \|w (DE-627)327815280 \|w (DE-600)2045049-7 \|x 17515823 \|7 nnns
773	1	8	\|g volume:63 \|g year:1995 \|g number:3 \|g pages:325-344
856	4	0	\|u https://www.jstor.org/stable/1403483 \|3 Volltext
856	4	0	\|u https://doi.org/10.2307/1403483 \|3 Volltext
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