Evidence map›Paper›PMID 29977100›Full record

ArticleStatistics & probability letters2018

A practical guide to big data.

Ekaterina Smirnova, Andrada Ivanescu, Jiawei Bai, Ciprian M Crainiceanu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Statistics & probability letters, 2018. 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.

Ekaterina SmirnovaAssistant Professor, Department of Mathematical Sciences, University of Montana, 32 Campus Dr, Missoula, MT 59812.
Andrada IvanescuAssistant Professor, Department of Mathematical Sciences, Montclair University, 1 Normal Avenue Montclair, NJ 07043.
Jiawei BaiAssistant Scientist, Department of Biostatistics, Johns Hopkins University, 615 N. Wolfe St. Baltimore, MD 21205 USA.
Ciprian M CrainiceanuProfessor, Department of Biostatistics, Johns Hopkins University, 615 N. Wolfe St. Baltimore, MD 21205 USA.

Funding

Statistical Methods for Multilevel Multivariate Functional StudiesR01NS060910 · NINDS · JOHNS HOPKINS UNIVERSITY · PI Ciprian M Crainiceanu · 2009 to 2026
$8.3M
Statistical methods for analyzing objectively measured physical activity dataR01HL130483 · NHLBI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Chongzhi Di · 2016 to 2026
$4.4M
Statistical methods for biosignals with varying domainsR01HL123407 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI CRAINICEANU, CIPRIAN M · 2014 to 2017
$1.6M
NHLBI NIH HHS R01 HL123407NHLBI NIH HHS R01 HL130483NINDS NIH HHS R01 NS060910
6 · The paper itself

Abstract

Big Data is increasingly prevalent in science and data analysis. We provide a short tutorial for adapting to these changes and making the necessary adjustments to the academic culture to keep Biostatistics truly impactful in scientific research.

Identifiers

PMID29977100
PMCPMC6028050

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.