Philip D. Waggoner

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Indrajeet PatilPreisenergie GmbHVerified email at preisenergie.de
Dominique MakowskiUniversity of Sussex, Brighton, UKVerified email at sussex.ac.uk
Mattan S. Ben-ShacharVerified email at msbstats.info
Daniel LüdeckeInstitut für Medizinische Soziologie, Universitätsklinikum Hamburg-EppendorfVerified email at uke.de
Ryan KennedyUniversity of HoustonVerified email at uh.edu
Scott CliffordAssociate Professor, Texas A&M UniversityVerified email at uh.edu
Rémi ThériaultPhD Student, Université du Québec à Montréal (MA, McGill University)Verified email at courrier.uqam.ca
Brenton M. WiernikMeta, Demography and Survey ScienceVerified email at usf.edu
Nicholas WinterAssociate Professor of Politics, University of VirginiaVerified email at virginia.edu
Jonathan A. SolisAidData Reserach Lab @ The College of William & MaryVerified email at aiddata.wm.edu
Samuel FrederickPh.D. Candidate, Department of Political Science, Columbia UniversityVerified email at columbia.edu
Myriam ShiranPostdoctoral Research Associate, Purdue UniversityVerified email at purdue.edu
Hayden LePhD Student, University of MichiganVerified email at umich.edu
Brandon RottinghausProfessor of Political Science, University of HoustonVerified email at uh.edu
Marc Lavielleresearch director, Inria SaclayVerified email at inria.fr
Adam L. OzerVerian | London School of Economics | MAHD Lab (University of Houston)Verified email at veriangroup.com
Tyler Burleigh
Matthew WardBaldwin Wallace UniversityVerified email at umich.edu

Philip D. Waggoner

Colorado School of Mines

Verified email at mines.edu - Homepage


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
performance: An R package for assessment, comparison and testing of statistical models D Lüdecke, MS Ben-Shachar, I Patil, P Waggoner, D Makowski Journal of Open Source Software 6 (60), 2021	2652	2021
Are samples drawn from Mechanical Turk valid for research on political ideology? S Clifford, RM Jewell, PD Waggoner Research & Politics 2 (4), 2053168015622072, 2015	856	2015
The shape of and solutions to the MTurk quality crisis R Kennedy, S Clifford, T Burleigh, PD Waggoner, R Jewell, NJG Winter Political Science Research and Methods 8 (4), 614-629, 2020	697	2020
Performance: assessment of regression models performance D Lüdecke, D Makowski, P Waggoner, I Patil R package version 0.4 5, 2020	555	2020
performance: Assessment of regression models performance. R Package Version 0.4. 7 D Lüdecke, D Makowski, P Waggoner, I Patil Appl Stat Using R 440, 5, 2020	124	2020
Insight: A unified interface to access information from model objects in R D Lüdecke, PD Waggoner, D Makowski Journal of Open Source Software 4 (38), 1412, 2019	119	2019
Compute and interpret indices of effect size M Ben-Shachar, D Makowski, D Lüdecke CRAN [online serial], 2020	105	2020
see: an R package for visualizing statistical models D Lüdecke, I Patil, MS Ben-Shachar, BM Wiernik, P Waggoner, ... Journal of Open Source Software 6 (64), 3393, 2021	62	2021
Detecting fraud in online surveys by tracing, scoring, and visualizing IP addresses PD Waggoner, R Kennedy, S Clifford Journal of Open Source Software 4 (37), 1285, 2019	56	2019
Trust in public policy algorithms RP Kennedy, PD Waggoner, MM Ward The Journal of Politics 84 (2), 1132-1148, 2022	42	2022
Assessment, testing and comparison of statistical models using R D Lüdecke, MS Ben-Shachar, I Patil, P Waggoner, D Makowski Journal of Open Source Software 6 (59), 3112, 2021	41	2021
Assessment of regression models performance. CRAN D Lüdecke, D Makowski, P Waggoner, I Patil, MS Ben-Shachar CRAN, 2020	40	2020
easystats: Framework for easy statistical modeling, visualization, and reporting D Lüdecke, MS Ben-Shachar, I Patil, BM Wiernik, D Makowski Repository CRAN, 2022	36	2022
Package “performance” D Lüdecke, D Makowski, P Waggoner, I Patil, MS Ben-Shachar CRAN. https://cran. r-project. org/web/packages/performance/index. html, 2019	25	2019
Measuring media freedom: An Item Response Theory analysis of existing indicators JA Solis, PD Waggoner British Journal of Political Science 51 (4), 1685-1704, 2021	22	2021
Unsupervised machine learning for clustering in political and social research PD Waggoner Elements in Quantitative and Computational Methods for the Social Sciences, 2020	21	2020
Package ‘effectsize’ MS Ben-Shachar, D Makowski, D Lüdecke, I Patil, BM Wiernik, K Kelley, ...	19	2022
See: Visualisation toolbox for’easystats’ and extra geoms, themes and color palettes for’ggplot2’ D Lüdecke, MS Ben-Shachar, P Waggoner, D Makowski R package version 0.5 1, 2020	18	2020
Uncovering the online social structure surrounding COVID-19 PD Waggoner, RY Shapiro, S Frederick, M Gong Journal of Social Computing 2 (2), 157-165, 2021	17	2021
Do constituents influence issue-specific bill sponsorship? PD Waggoner American Politics Research 47 (4), 709-738, 2019	17	2019

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