Count-Regression-Based Empirical Causal Analysis from a Potential Outcomes Perspective: Accounting for Boundedness, Discreteness, Dispersion and Unobservable Confounding

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Publication Details

Journal
IUScholarWorks (Indiana University)
Published
2025-08-29
DOI
https://doi.org/10.7912/qp14-yv68
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Count-Regression-Based Empirical Causal Analysis from a Potential Outcomes Perspective: Accounting for Boundedness, Discreteness, Dispersion and Unobservable Confounding

IUScholarWorks (Indiana University)
Geochemistry and Geologic Mapping
article

Count-Regression-Based Empirical Causal Analysis from a Potential Outcomes Perspective: Accounting for Boundedness, Discreteness, Dispersion and Unobservable Confounding

article en

Abstract

No abstract available for this paper.
IUScholarWorks (Indiana University)
Indiana University Indianapolis (US), Indiana University – Purdue University Indianapolis (US)
Reduced inequalities
Openalex Percentile: Top 59%
Geochemistry and Geologic Mapping
DOIOpen Access PDFOpenAlex
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Count-Regression-Based Empirical Causal Analysis from a Potential Outcomes Perspective: Accounting for Boundedness, Discreteness, Dispersion and Unobservable Confounding · IUScholarWorks (Indiana University) (2025) | TGRS Research Map | TGRS