Search 250 million research papers

Data cleaning

Jelte Wicherts, Linda Dominguez Alvarez, Michèle B. Nuijten et al. · OSF Preprints (OSF Preprints) · 2017

Cited by 0Open access

Data cleaning.

Maja E. Marcus (10232903), Cara Ebert (6416216), Pascal Geldsetzer (549621) et al. · Figshare · 2021

Cited by 0Open access

Data cleaning

Harutyunyan, Naira · Figshare · 2025

An introduction to data cleaning self-report data for quantitative psychology research using SPSS software.

Cited by 0Open access

Data cleaning

Robert Nisbet, Keith McCormick, Gary Miner · Elsevier eBooks · 2025

Cited by 0

Data cleaning

Harutyunyan, Naira · Figshare · 2025

Materials from an invited presentation for the Queer and Trans Psychological Inclusion <em>y Equidad</em> (QTPIE) Lab at California State University Northridge. Materials have previously been shared online elsewhere, but are published here for convenience. <br> Date of initial presentation: 2025, February 21st

Cited by 0Open access

Data cleaning

Michèle B. Nuijten, Marcel A.L.M. van Assen, Jelte Wicherts et al. · OSF Preprints (OSF Preprints) · 2017

Cited by 0

Cleaning data

2006

Cited by 0

Cleaning Data

Peng Zhao · 2023

Cited by 0

Data Cleaning

Thompson, Ashley · Open Science Framework · 2023

Cited by 0Open access

Data Cleaning

Jeri Elizabeth Wieringa · OSF Preprints (OSF Preprints) · 2018

Cited by 0

Data Cleaning

Goben, Abigail H, Asher, Andrew, Smale, Maura et al. · OSF Preprints (OSF Preprints) · 2019

Cited by 1Open access

Data cleaning

Harutyunyan, Naira · Figshare · 2025

An introduction to data cleaning self-report data for quantitative psychology research using SPSS software.

Cited by 0Open access

Data cleaning.

Bente Øvrebø (8563419), Ingunn H. Bergh (11226205), Tonje H. Stea (11226208) et al. · Figshare · 2021

Cited by 0Open access

Cleaning Data

2011

Cited by 0

Data Cleaning

Vanderbilt University Press eBooks · 2015

Cited by 2

Data cleaning

Olivia Christiano · OSF Preprints (OSF Preprints) · 2022

Cited by 0Open access

Data Cleaning

James Spottiswoode, Dick Bierman, Dean Radin · OSF Preprints (OSF Preprints) · 2021

Cited by 0

Data Cleaning

UiT The Arctic University Of Norway · Zenodo (CERN European Organization for Nuclear Research) · 2023

Course material for the webinar “Data Cleaning”, part of a webinar series on research data management (RDM) organized by UiT The Arctic University of Norway. For more information, please visit: site.uit.no/rdmtraining

Cited by 0Open access

Data Cleaning

Bierman, Dick, Spottiswoode, James, Radin, Dean · Open Science Framework · 2021

Cited by 0Open access

Data cleaning.

Marissa E. Renardy (14670558), Craig Gillen (14670561), Zhenhua Yang (150675) et al. · Figshare · 2023

&lt;div&gt;&lt;p&gt;Tuberculosis (TB) elimination in the United States remains elusive, and community-specific, localized intervention strategies may be necessary to meet elimination goals. A better understanding of the genotypic diversity of Mtb, the population subgroups affected by different TB strains, and differences in disease presentation associated with these strains can aid in identifying risk groups and designing tailored interventions. We analyze TB incidence and genotype data from all Arkansas counties over an 11-year time span from 2010 through 2020. We use statistical methods and geographic information systems (GIS) to identify demographic and disease phenotypic characteristics that are associated with different Mtb genetic lineages in the study area. We found the following variables to be significantly associated with genetic lineage (p&lt;0.05): patient county, patient birth country, patient ethnicity, race, IGRA result, disease site, chest X-ray result, whether or not a case was identified as part of a cluster, patient age, occupation risk, and date arrived in the US. Different Mtb lineages affect different subpopulations in Arkansas. Lineage 4 (EuroAmerican) and Lineage 2 (East Asian) are most prevalent, although the spatial distributions differ substantially, and lineage 2 (East Asian) is more frequently associated with case clusters. The Marshallese remain a particularly high-risk group for TB in Arkansas.&lt;/p&gt;&lt;/div&gt;

Cited by 0Open access