Open Access. Powered by Scholars. Published by Universities.®
Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Adult (1)
- Age factors (1)
- Aged (1)
- Analysis of variance (1)
- Environment design (1)
-
- Female (1)
- Home range (1)
- Home range analysis (1)
- Humans (1)
- Linear models (1)
- Logistic models (1)
- Male (1)
- Mechanistic home range models (1)
- Middle aged (1)
- Residence characteristics (1)
- Resource selection analysis (1)
- Sex factors (1)
- Spatially explicit space-use (1)
- Statistics & numerical data (1)
- Theoretical (1)
- Walking (1)
- Washington (1)
Articles 1 - 2 of 2
Full-Text Articles in Social and Behavioral Sciences
Mechanistic Home Range Models And Resource Selection Analysis: A Reconciliation And Unification, Paul R. Moorcroft, Alex Barnett
Mechanistic Home Range Models And Resource Selection Analysis: A Reconciliation And Unification, Paul R. Moorcroft, Alex Barnett
Dartmouth Scholarship
In the three decades since its introduction, resource selection analysis (RSA) has become a widespread method for analyzing spatial patterns of animal relocations obtained from telemetry studies. Recently, mechanistic home range models have been proposed as an alternative framework for studying patterns of animal space-use. In contrast to RSA models, mechanistic home range models are derived from underlying mechanistic descriptions of individual movement behavior and yield spatially explicit predictions for patterns of animal space-use. In addition, their mechanistic underpinning means that, unlike RSA, mechanistic home range models can also be used to predict changes in space-use following perturbation. In this …
Using Built Environment Characteristics To Predict Walking For Exercise, Gina S. Lovasi, Anne V. Moudon, Amber L. Pearson, Philip M. Hurvitz, Eric B. Larson, David S. Siscovick, Ethan M. Berke
Using Built Environment Characteristics To Predict Walking For Exercise, Gina S. Lovasi, Anne V. Moudon, Amber L. Pearson, Philip M. Hurvitz, Eric B. Larson, David S. Siscovick, Ethan M. Berke
Dartmouth Scholarship
Environments conducive to walking may help people avoid sedentary lifestyles and associated diseases. Recent studies developed walkability models combining several built environment characteristics to optimally predict walking. Developing and testing such models with the same data could lead to overestimating one's ability to predict walking in an independent sample of the population. More accurate estimates of model fit can be obtained by splitting a single study population into training and validation sets (holdout approach) or through developing and evaluating models in different populations. We used these two approaches to test whether built environment characteristics near the home predict walking for …