Main Title |
Parametric and nonparametric logistic regressions for prediction of presence/absence of an amphibian / |
Author |
Nash, Maliha S. ;
Bradford, D.
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Other Authors |
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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
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Internet Access |
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Holdings |
Library |
Call Number |
Additional Info |
Location |
Last Modified |
Checkout Status |
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. |
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07/26/2022 |
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Collation |
40 pages : illustrations ; 28 cm |
Abstract |
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. |
Notes |
"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." |