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Academic Articles & Research Papers
Showing 17 of 17 academic articles
James N. Druckman, DONALD PHILIP GREEN, James H. Kuklinski, Arthur Lupia • Cambridge University Press eBooks
(2011)
In his 1909 American Political Science Association presidential address, A. Lawrence Lowell (1910) advised the fledgling discipline against following the model of the natural sciences: “We are limited by the impossibility of experiment. Pol...
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DOI: https://doi.org/10.1017/cbo9780511921452.001
Rebecca B. Morton, Kenneth C. Williams • Cambridge University Press eBooks
(2010)
Increasingly, political scientists use the term 'experiment' or 'experimental' to describe their empirical research. One of the primary reasons for doing so is the advantage of experiments in establishing causal inferences. In this book, Re...
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DOI: https://doi.org/10.1017/cbo9780511762888
Rebecca B. Morton, Kenneth C. Williams • Oxford University Press eBooks
(2009)
Abstract This article mentions that the number of experiments has increased dramatically in political science in the last thirty-five years because of their power for making causal inferences. It directly confronts the Achilles heel of expe...
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DOI: https://doi.org/10.1093/oxfordhb/9780199286546.003.0014
Paul Pennings, Hans Keman, Jan Kleinnijenhuis • SAGE Publications Ltd eBooks
(2006)
PART ONE: COMPARATIVE METHODOLOGY - Hans Keman Comparative Methodology and Statistics in Political Science The Comparative Approach Theory and Method Meaning and Use of the Comparative Method Research Design PART TWO: STATISTICS IN POLITICA...
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DOI: https://doi.org/10.4135/9781849209038
Sihan Xiong, Yiwei Fu, Asok Ray • Entropy
(2018)
This paper presents a nonparametric regression model of categorical time series in the setting of conditional tensor factorization and Bayes network. The underlying algorithms are developed to provide a flexible and parsimonious representat...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/e20060396
Albert Whata, Charles Chimedza • IEEE Access
(2022)
Logistic regression (LR) is a popular method that is used for estimating causal effects in observational studies using propensity scores. We examine the use of deep learning models such as the deep neural network (DNN), PropensityNet (PN), ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2021.3140189
Szyszko Magdalena, Kliber Agata, Motuzka Olena • International Journal of Management and Economics
(2025)
We use causal inference analysis with Bayesian structural time series modelling to identify the changes in the direction and amplitude of Ukrainian and Polish consumer and professional inflation expectations after the outbreak of war in Ukr...
DOAJ
Open Access (DOAJ)
DOI: 10.2478/ijme-2025-0012
Yu Li, Juan Chai, Jinjuan Chen, Jiayin Du et al. • Scientific Reports
(2025)
Abstract The potential impact of heavy metal exposure on the progression of diabetic kidney disease (DKD) remains a subject of scientific inquiry. While some studies have hinted at a correlation, definitive evidence is still lacking. It is ...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-025-23843-w
Sabrina Chiodo, Sonia M. Grandi, Jessica Gronsbell, Laura C. Rosella • International Journal of Population Data Science
(2026)
Introduction
Perinatal outcomes are shaped by clinical, social, and environmental factors, yet Canada lacks a nationally representative pregnancy cohort capturing these influences at the individual-level. This gap has limited the ability to...
DOAJ
Open Access (DOAJ)
DOI: 10.23889/ijpds.v8i6.3358
Roger Detels, Robert Beaglehole, Mary Ann Lansang, Martin C. Gulliford • RePEc: Research Papers in Economics
(2011)
SECTION 1: THE DEVELOPMENT OF THE DISCIPLINE OF PUBLIC HEALTH 1.1 The scope and concerns of public health 1.2 The history and development of public health in high-income countries 1.3 The history and development of public health in low- and...
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Elouanes Khelifi, Amir Saki, Sousso Kelouwani, Usef Faghihi • Applied Food Research
(2026)
The production of processed foods and animal nutrition requires precise control over product characteristics to ensure consistent quality. Unexpected fluctuations in key parameters, particularly humidity, can lead to significant financial l...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.afres.2026.102698
Jong-Min Kim • Axioms
(2025)
This paper presents the use of Copula-based deep learning with Horvitz–Thompson (HT) weights and inverse probability of treatment weighting (IPTW) for estimating propensity scores in causal inference problems. This study compares the perfor...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/axioms14060458
Qiang Zhao, Rundong Guo, Xiaowei Feng, Weifeng Hu et al. • Mathematics
(2022)
Legal judgement prediction (LJP) is a crucial part of legal AI, and its goal is to predict the outcome of a case based on the information in the description of criminal facts. This paper proposes a decision prediction method based on causal...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/math10132281
Maximilian Pichler, Florian Hartig • Methods in Ecology and Evolution
(2023)
Abstract The popularity of machine learning (ML), deep learning (DL) and artificial intelligence (AI) has risen sharply in recent years. Despite this spike in popularity, the inner workings of ML and DL algorithms are often perceived as opa...
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DOI: https://doi.org/10.1111/2041-210x.14061
M.Á. Luján, R. Young-Morrison, V. Kashtelyan, G. Loewinger et al. • Cell Reports
(2026)
Summary: Quickly adapting behavior to changing environments is key for survival. Brain dopamine signals reinforce actions that procure rewards and avoid adverse outcomes. However, the molecular mechanisms within the circuits that actuate th...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.celrep.2026.117298
Mario D. Molina, Filiz Garip • Annual Review of Sociology
(2019)
Machine learning is a field at the intersection of statistics and computer science that uses algorithms to extract information and knowledge from data. Its applications increasingly find their way into economics, political science, and soci...
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Open Access
DOI: https://doi.org/10.1146/annurev-soc-073117-041106
Bernhard Schölkopf • ACM eBooks
(2022)
Graphical causal inference as pioneered by Judea Pearl arose from research on artificial intelligence (AI), and for a long time had little connection to the field of machine learning. This article discusses where links have been and should ...
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Open Access
DOI: https://doi.org/10.1145/3501714.3501755