The potential and perils of preprocessing: building new foundations

DOI10.3150/13-BEJSP16zbMath1440.62019arXiv1309.6790OpenAlexW2023338600MaRDI QIDQ373524

Alexander W. Blocker, Xiao-Li Meng

Publication date: 17 October 2013

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1309.6790

zbMATH Keywords

data compressionmeasurement errormultiple imputationdata repositoriesmultiphase inferencestatistical principles

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Sampling theory, sample surveys (62D05) Foundations and philosophical topics in statistics (62A01) Missing data (62D10)

Related Items (5)

Conducting highly principled data science: a statistician's job and joy ⋮ Nonstandard conditionally specified models for nonignorable missing data ⋮ Multiple Improvements of Multiple Imputation Likelihood Ratio Tests ⋮ Discussion: The Q‐q Dynamic for Deeper Learning and Research ⋮ Multi-way blockmodels for analyzing coordinated high-dimensional responses

Uses Software

• Bioconductor
• gcrma
• limma

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