Record Display for the EPA National Library Catalog


Main Title Parametric and nonparametric logistic regressions for prediction of presence/absence of an amphibian /
Author Nash, Maliha S. ; Bradford, D.
Other Authors
Author Title of a Work
Bradford, David F.
CORP Author Environmental Protection Agency, Las Vegas, NV. National Exposure Research Lab.
Publisher U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, Environmental Sciences Division,
Year Published 2001
Report Number EPA 600-R-01-081; NERL-LV-ESD-01-128; PB2002102297
Stock Number PB2002-102297
OCLC Number 48562693
Additional Subjects Logistic regression ; Amphibians ; Reference manuals ; Statistical methods ; Independent variables ; Statistical analysis ; Habitat variables ; Dependent binary response variable
Internet Access
Description Access URL
Library Call Number Additional Info Location Last
ELBD ARCHIVE EPA 600-R-01-081 Received from HQ AWBERC Library/Cincinnati,OH 10/04/2023
NTIS  PB2002-102297 Some EPA libraries have a fiche copy filed under the call number shown. 07/26/2022
Collation 40 pages : illustrations ; 28 cm
The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response variable (e.g., presence/absence) and a set of independent variables are provided step by step for use by scientists who are not statisticians. Details of such statistical analyses and their assumptions are often omitted from published literature, yet such details are essential to the proper conduct of statistical analyses and interpretation of results. In this report, we use a data set for amphibian presence/absence and associated habitat variables as an example.
"October 2001." "EPA 600-R-01-081." Includes bibliographical references (pages 26-27). "Full title: Parametric and nonparametric (MARS; multivariate additive regression splines) logistic regressions for prediction of dichotomous response variable with an example for presence/absence of an amphibian."