Resource Image

Modeling Changes in Probability of Presence of Myotis lucifugus Due to White Nose Syndrome: An Introduction to Logistic Regression in R

Author(s): Mary Roseblock

Virginia Commonwealth University

720 total view(s), 500 download(s)

0 comment(s) (Post a comment)

Summary:
In this lesson, students will learn more about the wildlife disease known as white nose syndrome and how it affects certain bat species more than others. Students will learn about the important ecosystem services bats provide and why bat…

more

In this lesson, students will learn more about the wildlife disease known as white nose syndrome and how it affects certain bat species more than others. Students will learn about the important ecosystem services bats provide and why bat conservation is important to overall ecosystem health. To demonstrate the negative impacts of WNS on Myotis lucifugus, students will learn how to fit a logistic regression model in R and analyze how the probability of catching this species has decreased since the introduction of WNS in West Virginia. Students will evaluate the fit of the model using a diagnostic plot and the summary output, and they will learn how to interpret the coefficients. This lesson contains a short video introduction, student and instructor handouts, the curated data, and annotated student and instructor versions of the R code. The R-markdown and the lesson handout provide a step-by-step tutorial on how to do a logistic regression in R. The handouts are intended to compliment the original paper, and students will be prompted to answer questions about the paper itself and the R code.

Description

Using data from a previously published paper, Long-term changes in occurrence, relative abundance, and reproductive fitness of bat species in relation to arrival of White-nose Syndrome in West Virginia, USA, students will learn more about the impact WNS has had on certain bat species. This lesson will show students how to fit a logistic regression model, assess the fit of the model, and how to interpret the coefficients.

Notes

The final graphs in the instructor and student handouts were updated. The original graphs in the handouts were not jittered to match the R code. 

Cite this work