JSM 2005 Online Program

Abstract #302951

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	27
Type:	Contributed
Date/Time:	Sunday, August 7, 2005 : 2:00 PM to 3:50 PM
Sponsor:	Section on Statistical Education
Abstract - #302951
Title:	Interdisciplinary Undergraduate Research: Habitat Suitability Models of the Missouri Bladder-pod
Author(s):	Hyun-joo Kim*+
Companies:	Truman State University
Address:	100 Normal, Kirksville, MO, 63501, United States
Keywords:	Interdisciplinary undergraduate research ; Biometrics ; Missouri bladder-pod ; Logistic regression model ; Model validation ; Habitat suitability model
Abstract:	As an undergraduate liberal arts institution, Truman State University provides undergraduate students various research experiences. MBI (Mathematics Biology Initiative) and RLC (Research Learning Community) are two of the unique programs that support interdisciplinary undergraduate research in Biology and Math/Stat areas. As a part of MBI and programs funded by NSF, a statistics and biology professor and a mathematics and biology undergraduate student have been involved with the project to undertake a comprehensive habitat suitability model development and assessment of a federally threatened plant species, the Missouri bladder-pod (Lesquerella filiformis) collected at two spatial scales. The objectives of the project are building and comparing the qualities of habitat suitability models based on different statistical approaches, specifically parametric and nonparametric logistic regression modeling, and identifying the "best" model(s) and validating them using various existing and proposed validation methods. The resulting habitat suitability models then are used to assess how a model generated from one spatial scale performs in predicting at another scale.

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