Connor Donegan
Biographic Data
| ID | 1340417 |
|---|---|
| NAME | Connor Donegan |
| GIVEN NAMES | Connor |
| FAMILY NAME | Donegan |
| SIGNATURE | DONEGAN C |
| AFFILIATIONS | The University of Texas at Dallas |
| ORCID | 0000-0002-9698-5443 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Plausible Reasoning and Spatial‐Statistical Theory: A Critique of Recent Writings on “Spatial Confounding”
Statistical research on correlation with spatial data dates at least to Student's (W. S. Gosset's) 1914 paper on “the elimination of spurious correlation due to position in time and space.” Since 1968, much of this work has been organized around the concept of spatial autocorrelation (SA). A growing statistical literature is now organized around the concept of “spatial confounding” (SC) but is estranged from, and often at odds with, the SA litera…
Investigating Cancer Inequalities in Urbanizing Texas with Plausible Reasoning
This article contributes to geographical methodology by presenting an epistemology of plausible reasoning (PR) as a complement to realist and reflexive frameworks for science. I introduce PR's theory of evidence, after Harold Jeffreys and George Pólya, and then extrapolate principles for nonexperimental study designs. This article leverages these principles to structure an investigation into the causes of a racial disparity in the colorectal canc…
Modeling Community Health with Areal Data: Bayesian Inference with Survey Standard Errors and Spatial Structure
Epidemiologists and health geographers routinely use small-area survey estimates as covariates to model areal and even individual health outcomes. American Community Survey (ACS) estimates are accompanied by standard errors (SEs), but it is not yet standard practice to use them for evaluating or modeling data reliability. ACS SEs vary systematically across regions, neighborhoods, socioeconomic characteristics, and variables. Failure to consider p…
Overlapping geographic clusters of food security and health: Where do social determinants and health outcomes converge in the U.S
We identified overlapping geographic clusters of food insecurity and health across U.S. counties to identify potential shared mechanisms for geographic disparities in health and food insecurity. By analyzing health variables compiled as part of the 2014 Robert Wood Johnson Foundation County Health Rankings, we constructed four health indices and compared their spatial patterns to spatial patterns found in food insecurity data obtained from 2014 F…
No prominent works on this page.
Overlapping geographic clusters of food security and health: Where do social determinants and health outcomes converge in the U.S
We identified overlapping geographic clusters of food insecurity and health across U.S. counties to identify potential shared mechanisms for geographic disparities in health and food insecurity. By analyzing health variables compiled as part of the 2014 Robert Wood Johnson Foundation County Health Rankings, we constructed four health indices and compared their spatial patterns to spatial patterns found in food insecurity data obtained from 2014 F…
Modeling Community Health with Areal Data: Bayesian Inference with Survey Standard Errors and Spatial Structure
Epidemiologists and health geographers routinely use small-area survey estimates as covariates to model areal and even individual health outcomes. American Community Survey (ACS) estimates are accompanied by standard errors (SEs), but it is not yet standard practice to use them for evaluating or modeling data reliability. ACS SEs vary systematically across regions, neighborhoods, socioeconomic characteristics, and variables. Failure to consider p…
Plausible Reasoning and Spatial‐Statistical Theory: A Critique of Recent Writings on “Spatial Confounding”
Statistical research on correlation with spatial data dates at least to Student's (W. S. Gosset's) 1914 paper on “the elimination of spurious correlation due to position in time and space.” Since 1968, much of this work has been organized around the concept of spatial autocorrelation (SA). A growing statistical literature is now organized around the concept of “spatial confounding” (SC) but is estranged from, and often at odds with, the SA litera…
Investigating Cancer Inequalities in Urbanizing Texas with Plausible Reasoning
This article contributes to geographical methodology by presenting an epistemology of plausible reasoning (PR) as a complement to realist and reflexive frameworks for science. I introduce PR's theory of evidence, after Harold Jeffreys and George Pólya, and then extrapolate principles for nonexperimental study designs. This article leverages these principles to structure an investigation into the causes of a racial disparity in the colorectal canc…
Mathematics (3 works) · Econometrics (2 works) · Geography (2 works) · Health disparities and outcomes (2 works) · Homelessness and Social Issues (2 works) · Sociology (2 works) · Spatial and Panel Data Analysis (2 works) · Statistics (2 works) · Agriculture (1 works) · Appalachia (1 works)