Evidence map›Paper›PMID 33122862›Full record

ArticleBiometrika2020

A Conditional Density Estimation Partition Model Using Logistic Gaussian Processes.

R D Payne, N Guha, Y Ding, B K Mallick

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biometrika, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

R D PayneEli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana 46285, U.S.A.
N GuhaDepartment of Mathematical Sciences, University of Massachusetts Lowell, 220 Pawtucket St, Lowell, Massachusetts 01854, U.S.A.
Y DingDepartment of Industrial and Systems Engineering, Texas A&M University, 3131 TAMU, College Station, Texas 77843-3131, U.S.A.
B K MallickDepartment of Statistics, Texas A&M University, 3143 TAMU, College Station, Texas 77843-3143, U.S.A.

Funding

Graph-based Bayesian analysis of Genomics and Proteomics DataR01CA194391 · NCI · TEXAS A&M UNIVERSITY · PI BALADANDAYUTHAPANI, VEERABHADRAN, MALLICK, BANI K · 2016 to 2020
$2.0M
NCI NIH HHS R01 CA194391
6 · The paper itself

Abstract

Conditional density estimation (density regression) estimates the distribution of a response variable

Identifiers

PMID33122862
PMCPMC7592629

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.