Evidence map›Paper›PMID 42238549›Full record

ArticleElectronic journal of statistics2015

Selecting massive variables using an iterated conditional modes/medians algorithm.

Vitara Pungpapong, Min Zhang, Dabao Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Electronic journal of statistics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Probabilistic single-particle cryo-EM ab initio 3D reconstruction in SIMPLE.Acta crystallographica. Section D, Structural biology · 2025
    Article
  4. Integrating Biological Knowledge Into Case-Control Analysis Through Iterated Conditional Modes/Medians Algorithm.Journal of computational biology : a journal of computational molecular cell biology · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Vitara PungpapongDepartment of Statistics, Faculty of Commerce and Accountancy, Chulalongkorn University, Bangkok, Thailand.
Min ZhangDepartment of Statistics, Purdue University, West Lafayette, IN 47907.
Dabao ZhangDepartment of Statistics, Purdue University, West Lafayette, IN 47907.

Funding

NEURAL MECHANISMS OF LONG-TERM CARDIOVASCULAR CONTROLR01HL064178 · NHLBI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI OSBORN, JOHN W · 2000 to 2007
$2.4M
Early Cancer Detection & Prognosis through GlycomicsU01CA128535 · NCI · TRUSTEES OF INDIANA UNIVERSITY · PI NOVOTNY, MILOS · 2007 to 2011
$1.9M
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
–
NCI NIH HHS U01 CA128535NHLBI NIH HHS N01 HC025195NHLBI NIH HHS R01 HL064178
6 · The paper itself

Abstract

Empirical Bayes methods are designed in selecting massive variables, which may be inter-connected following certain hierarchical structures, because of three attributes: taking prior information on model parameters, allowing data-driven hyperparameter values, and free of tuning parameters. We propose an iterated conditional modes/medians (ICM/M) algorithm to implement empirical Bayes selection of massive variables, while incorporating sparsity or more complicated

Indexed as

Empirical Bayes variable selectionhigh dimensional dataPrimary 62J05priorsecondary 62C12, 62F07sparsity

Identifiers

PMID42238549
PMCPMC13229566

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.