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Physical Sciences and Mathematics Commons™
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- Simulation (2)
- American ginseng (1)
- Biodiversity (1)
- Cryptic species (1)
- Generalized boosted modeling (1)
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- Habitat suitability model (1)
- Item properties (1)
- Limnonectes kuhlii (1)
- Linear logistic test model (1)
- Model misspecification (1)
- Molecular DNA (1)
- Morphology (1)
- Panax quinquefolius (1)
- Propensity score matching (1)
- Propensity score weighting (1)
- Quasi-experimental (1)
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- Rasch model (1)
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- Species complex (1)
- Species distribution model (1)
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Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Can Auxiliary Information Improve Rasch Estimation At Small Sample Sizes?, Derek Sauder
Can Auxiliary Information Improve Rasch Estimation At Small Sample Sizes?, Derek Sauder
Dissertations, 2020-current
The Rasch model is commonly used to calibrate multiple choice items. However, the sample sizes needed to estimate the Rasch model can be difficult to attain (e.g., consider a small testing company trying to pretest new items). With small sample sizes, auxiliary information besides the item responses may improve estimation of the item parameters. The purpose of this study was to determine if incorporating item property information (i.e., characteristics of the items related to item difficulty) in a random effects linear logistic test model (RE-LLTM) would improve estimation of item difficulty. A simulation study was conducted that varied sample size, …
Modeling Species Distribution And Habitat Suitability Of American Ginseng (Panax Quinquefolius) In Virginia, Jacob D. J. Peters
Modeling Species Distribution And Habitat Suitability Of American Ginseng (Panax Quinquefolius) In Virginia, Jacob D. J. Peters
Masters Theses, 2020-current
American ginseng (Panax quinquefolius) is a well-known and sought-after medicinal plant native to North America that is facing increased threat of extinction due to overharvesting, herbivory, and habitat loss. Species distribution and habitat suitability models may be valuable to landowners interested in sustainable harvest or to institutions interested in the conservation and restoration of the species. With unequal sampling efforts across a region of interest, it is likely that some locations with appropriate habitat may be misrepresented in model predictions. This study refined a state-derived species distribution model for ginseng through increased sampling effort across the Cumberland Plateau …
Splitting Up A Complex Mess: The Effectiveness Of Statistical Analysis On Delimiting Species Complexes, Sara N. Schoen
Splitting Up A Complex Mess: The Effectiveness Of Statistical Analysis On Delimiting Species Complexes, Sara N. Schoen
Masters Theses, 2020-current
Recent studies have highlighted a need for more refined tools in species delimitation. This is especially true when considering diversity within species complexes, where members are morphologically similar and traditional tools have thus far failed to provide clearly defined boundaries between species. This project seeks to refine our traditional tools of species delimitation and apply new tools to the challenges created by species complexes. The focus organisms of this study are the anurans of the Limnonectes kuhlii complex. This species complex comprises more than 25 species of stream frogs from Southeast Asia. Traditionally, morphometrics (particularly linear measures) has been the …
Propensity Score Matching And Generalized Boosted Modeling In The Context Of Model Misspecification: A Simulation Study, Briana G. Craig
Propensity Score Matching And Generalized Boosted Modeling In The Context Of Model Misspecification: A Simulation Study, Briana G. Craig
Masters Theses, 2020-current
In the absence of random assignment, researchers must consider the impact of selection bias – pre-existing covariate differences between groups due to differences among those entering into treatment and those otherwise unable to participate. Propensity score matching (PSM) and generalized boosted modeling (GBM) are two quasi-experimental pre-processing methods that strive to reduce the impact of selection bias before analyzing a treatment effect. PSM and GBM both examine a treatment and comparison group and either match or weight members of those groups to create new, balanced groups. The new, balanced groups theoretically can then be used as a proxy for the …