Evidence map›Paper›PMID 29200600›Full record

ArticleJournal of econometrics2017

Simultaneous treatment of unspecified heteroskedastic model error distribution and mismeasured covariates for restricted moment models.

Tanya P Garcia, Yanyuan Ma

Abstract read
In one paragraph

Article in Journal of econometrics, 2017. 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

2 authors.

Tanya P GarciaDepartment of Epidemiology and Biostatistics, Texas A&M University.
Yanyuan MaDepartment of Statistics, Pennsylvania State University.

Funding

Innovative Statistical Models for Development of First Huntington's Disease Progression Risk Assessment ToolK01NS099343 · NINDS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GARCIA, TANYA PAMELA · 2017 to 2019
$739k
NINDS NIH HHS K01 NS099343
6 · The paper itself

Abstract

We develop consistent and efficient estimation of parameters in general regression models with mismeasured covariates. We assume the model error and covariate distributions are unspecified, and the measurement error distribution is a general parametric distribution with unknown variance-covariance. We construct root-

Indexed as

Influence functionLinear operatorMeasurement errorNuisance tangent spaceRestricted moment model

Identifiers

PMID29200600
PMCPMC5708600

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.