A closer look at testing the ``no-treatment-effect hypothesis in a comparative experiment

DOI10.1214/15-STS513zbMath1332.62065arXiv1509.03108MaRDI QIDQ254464

Joseph B. Lang

Publication date: 8 March 2016

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1509.03108

zbMATH Keywords

permutation testscausal effectsFisher's exact testcompletely randomized designfinite-population sampling theoryFisher vs. NeymanHorvitz-Thompson estimatornonmeasurable probability samplepotential variablesprocess-based inferencerandomization testsrandomization-based inferenceselection-based inference

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Parametric hypothesis testing (62F03)

Related Items (2)

A paradox from randomization-based causal inference ⋮ An apparent paradox explained

Cites Work

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• Model assisted survey sampling
• Why randomize?
• Permutation methods: a basis for exact inference
• THE INTERPRETATION OF THE EFFECTS OF NON-ADDITIVITY IN THE LATIN SQUARE
• Statistics and Causal Inference
• A Unified Approach to Design of Experiments
• In Memoriam: Jerzy Neyman 1894–1981
• On the Two Different Aspects of the Representative Method: The Method of Stratified Sampling and the Method of Purposive Selection
• Causal Inference Using Potential Outcomes
• ON THE z-TEST IN RANDOMIZED BLOCKS AND LATIN SQUARES
• THE SIGNIFICANCE OF THE DIFFERENCE BETWEEN TWO MEANS WHEN THE POPULATION VARIANCES ARE UNEQUAL
• A Generalization of Sampling Without Replacement From a Finite Universe

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