David Kahle
Biographic Data
| ID | 4392633 |
|---|---|
| NAME | David Kahle |
| GIVEN NAMES | David |
| FAMILY NAME | Kahle |
| SIGNATURE | KAHLE D |
| AFFILIATIONS | Center for Occupational Research and Development |
| ORCID | 0000-0002-9999-1558 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 8 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2015 |
| H-INDEX | 1 |
A Bayesian Approach to Account for Misclassification and Overdispersion in Count Data
Count data are subject to considerable sources of what is often referred to as non-sampling error. Errors such as misclassification, measurement error and unmeasured confounding can lead to substantially biased estimators. It is strongly recommended that epidemiologists not only acknowledge these sorts of errors in data, but incorporate sensitivity analyses into part of the total data analysis. We extend previous work on Poisson regression models…
Ggmap: Spatial Visualization with ggplot2
In spatial statistics the ability to visualize data and models superimposed with their basic social landmarks and geographic context is invaluable. ggmap is a new tool which enables such visualization by combining the spatial information of static maps from Google Maps, OpenStreetMap, Stamen Maps or CloudMade Maps with the layered grammar of graphics implementation of ggplot2. In addition, several new utility functions are introduced which allow …
How Risk Perceptions Influence Evacuations from Hurricanes and Compliance with Government Directives
In this study we present evidence supporting the view that people's perceived risk of hurricane‐related hazards can be reduced to a single seriousness score that spans different hurricane‐induced risk types and that compliant behavior with official advisories is strongly dependent on whether one perceives a high risk with respect to any type of hurricane‐related hazards. Our analysis suggests that people are less sensitive to risk type than they …
How Risk Perceptions Influence Evacuations from Hurricanes and Compliance with Government Directives
In this study we present evidence supporting the view that people's perceived risk of hurricane‐related hazards can be reduced to a single seriousness score that spans different hurricane‐induced risk types and that compliant behavior with official advisories is strongly dependent on whether one perceives a high risk with respect to any type of hurricane‐related hazards. Our analysis suggests that people are less sensitive to risk type than they …
Ggmap: Spatial Visualization with ggplot2
In spatial statistics the ability to visualize data and models superimposed with their basic social landmarks and geographic context is invaluable. ggmap is a new tool which enables such visualization by combining the spatial information of static maps from Google Maps, OpenStreetMap, Stamen Maps or CloudMade Maps with the layered grammar of graphics implementation of ggplot2. In addition, several new utility functions are introduced which allow …
How Risk Perceptions Influence Evacuations from Hurricanes and Compliance with Government Directives
In this study we present evidence supporting the view that people's perceived risk of hurricane‐related hazards can be reduced to a single seriousness score that spans different hurricane‐induced risk types and that compliant behavior with official advisories is strongly dependent on whether one perceives a high risk with respect to any type of hurricane‐related hazards. Our analysis suggests that people are less sensitive to risk type than they …
A Bayesian Approach to Account for Misclassification and Overdispersion in Count Data
Count data are subject to considerable sources of what is often referred to as non-sampling error. Errors such as misclassification, measurement error and unmeasured confounding can lead to substantially biased estimators. It is strongly recommended that epidemiologists not only acknowledge these sorts of errors in data, but incorporate sensitivity analyses into part of the total data analysis. We extend previous work on Poisson regression models…
Computer Science (3 works) · Medicine (2 works) · Actuarial science (1 works) · Artificial Intelligence (1 works) · Artificial Intelligence (1 works) · Bayesian probability (1 works) · Business (1 works) · Cartography (1 works) · Census and Population Estimation (1 works) · Compliance (psychology (1 works)