Evidence map›Paper›PMID 35529268›Full record

ArticleComputational and mathematical methods in medicine2022

Cross-Sectional Analysis of Impulse Indicator Saturation Method for Outlier Detection Estimated via Regularization Techniques with Application of COVID-19 Data.

Sara Muhammadullah, Amena Urooj, Muhammad Hashim Mengal, Shahzad Ali Khan, Fereshteh Khalaj

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.5field-weighted citation impact, top 17% of its field
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

0 citing papers in PubMed, 6 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 4 institutions in 2 countries.

Sara MuhammadullahDepartment of Economics and Econometrics, Pakistan Institute of Development Economics, Islamabad, Pakistan.ORCID https://orcid.org/0000-0002-7246-0431
Amena UroojDepartment of Economics and Econometrics, Pakistan Institute of Development Economics, Islamabad, Pakistan.
Muhammad Hashim MengalWorld Health Organization, Pakistan.
Shahzad Ali KhanVice-Chancellor of Health Services Academy Islamabad, Pakistan.
Fereshteh KhalajDepartment of Mathematics and Statistics, Parand and Robat Karim Branch, Islamic Azad University, Tehran, Iran.ORCID https://orcid.org/0000-0001-6979-3756
Pakistan Institute of Development Economics · PKHealth Services Academy · PKIslamic Azad University of Parand · IRWorld Health Organization - Pakistan · PK

Funding

World Health Organization 001
6 · The paper itself

Abstract

Impulse indicator saturation is a popular method for outlier detection in time series modeling, which outperforms the least trimmed squares (LTS), M-estimator, and MM-estimator. However, using the IIS method for outlier detection in cross-sectional analysis has remained unexplored. In this paper, we probe the feasibility of the IIS method for cross-sectional data. Meanwhile, we are interested in forecasting performance and covariate selection in the presence of outliers. IIS method uses Autometrics techniques to estimate the covariates and outlier as the number of covariates

Indexed as

COVID-19Computer SimulationCross-Sectional StudiesHumansLeast-Squares AnalysisResearch Design

Identifiers

PMID35529268
PMCPMC9073553
OpenAlexW4229077929

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.