A Wissler
Biographic Data
| ID | 54979 |
|---|---|
| NAME | A Wissler |
| GIVEN NAMES | A |
| FAMILY NAME | Wissler |
| SIGNATURE | WISSLER A |
| AFFILIATIONS | Department of Anthropology McMaster University Hamilton Canada |
| ORCID | 0000-0001-7129-5342 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 1 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
The Hamann‐Todd Human Osteological Collection
Imputation methods for mixed datasets in bioarchaeology
Missing data is a prevalent problem in bioarchaeological research and imputation could provide a promising solution. This work simulated missingness on a control dataset (481 samples × 41 variables) in order to explore imputation methods for mixed data (qualitative and quantitative data). The tested methods included Random Forest (RF), PCA/MCA, factorial analysis for mixed data (FAMD), hotdeck, predictive mean matching (PMM), random samples from …
Missing data in bioarchaeology II
Missing data in bioarchaeology I
Demographic and Evolutionary Consequences of Pandemic Diseases
The ongoing COVID-19 pandemic has justifiably captured the attention of people around the world since late 2019. It has produced in many people a new perspective on or, indeed, a new realization about our potential vulnerability to emerging infectious diseases. However, our species has experienced numerous catastrophic disease pandemics in the past, and in addition to concerns about the harm being produced during the pandemic and the potential lo…
Imputation methods for mixed datasets in bioarchaeology
Missing data is a prevalent problem in bioarchaeological research and imputation could provide a promising solution. This work simulated missingness on a control dataset (481 samples × 41 variables) in order to explore imputation methods for mixed data (qualitative and quantitative data). The tested methods included Random Forest (RF), PCA/MCA, factorial analysis for mixed data (FAMD), hotdeck, predictive mean matching (PMM), random samples from …
Demographic and Evolutionary Consequences of Pandemic Diseases
The ongoing COVID-19 pandemic has justifiably captured the attention of people around the world since late 2019. It has produced in many people a new perspective on or, indeed, a new realization about our potential vulnerability to emerging infectious diseases. However, our species has experienced numerous catastrophic disease pandemics in the past, and in addition to concerns about the harm being produced during the pandemic and the potential lo…
Missing data in bioarchaeology II
Missing data in bioarchaeology I
Imputation methods for mixed datasets in bioarchaeology
Missing data is a prevalent problem in bioarchaeological research and imputation could provide a promising solution. This work simulated missingness on a control dataset (481 samples × 41 variables) in order to explore imputation methods for mixed data (qualitative and quantitative data). The tested methods included Random Forest (RF), PCA/MCA, factorial analysis for mixed data (FAMD), hotdeck, predictive mean matching (PMM), random samples from …
The Hamann‐Todd Human Osteological Collection
Forensic Anthropology and Bioarchaeology Studies (3 works) · Missing data (3 works) · Statistical Methods and Bayesian Inference (3 works) · Bioarchaeology (2 works) · listwise deletion (2 works) · missing data imputation (2 works) · pairwise deletion (2 works) · Statistical Methods in Epidemiology (2 works) · best practices (1 work) · causes of death (1 work)