Evidence map›Paper›PMID 33762800›Full record

ArticleJournal of nonparametric statistics2020

Local polynomial regression for pooled response data.

Dewei Wang, Xichen Mou, Xiang Li, Xianzheng Huang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of nonparametric statistics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Additive partially linear model for pooled biomonitoring data.Computational statistics & data analysis · 2024
    Article
  2. Article
  3. Local polynomial regression for pooled response data.Journal of nonparametric statistics · 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

4 authors.

Dewei WangDepartment of Statistics, University of South Carolina, Columbia, South Carolina, U.S.A.
Xichen MouDivision of Epidemiology, Biostatistics, and Environmental Health, University of Memphis, Memphis, Tennessee, U.S.A.
Xiang LiJPMorgan Chase, Jersey City, New Jersey 07310, U.S.A.
Xianzheng HuangDepartment of Statistics, University of South Carolina, Columbia, South Carolina, U.S.A.

Funding

Flexible biomarker evaluation through a cost-effective data collection mechanismR03AI135614 · NIAID · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI WANG, DEWEI · 2019 to 2020
$147k
NIAID NIH HHS R03 AI135614
6 · The paper itself

Abstract

We propose local polynomial estimators for the conditional mean of a continuous response when only pooled response data are collected under different pooling designs. Asymptotic properties of these estimators are investigated and compared. Extensive simulation studies are carried out to compare finite sample performance of the proposed estimators under various model settings and pooling strategies. We apply the proposed local polynomial regression methods to two real-life applications to illustrate practical implementation and performance of the estimators for the mean function.

Indexed as

62G0862G20cross validationhomogeneous poolingrandom pooling

Identifiers

PMID33762800
PMCPMC7986571

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.