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Nomograms Aid Interpretation of Complex Regression Models
Robert A. Gitzen and Joshua J. Millspaugh
The Journal of Wildlife Management
Vol. 71, No. 7 (Sep., 2007), pp. 2438-2443
Stable URL: http://www.jstor.org/stable/4496360
Page Count: 6
You can always find the topics here!Topics: Nomographs, Regression analysis, Ecological modeling, Forage, Logistic regression, Elks, Wildlife management, Ecology, Wildlife ecology, Statistical models
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Ecologists often develop complex regression models that include multiple categorical and continuous variables, interactions among predictors, and nonlinear relationships between the response and predictor variables. Nomograms, which are graphical devices for presenting mathematical functions and calculating output values, can aid biologists in interpreting and presenting these complex models. To illustrate benefits of nomograms, we developed a logistic regression model of elk (Cervus elaphus) resource selection. With this model, we demonstrated how a nomogram helps scientists and managers interpret interactions among variables, compare the relative biological importance of variables, and examine predicted shapes of relationships (e.g., linear vs. nonlinear) between response and predictor variables. Although our example focused on logistic regression, nomograms are equally useful for other linear and nonlinear models. Regardless of the approach used for model development, nomograms and other graphical summaries can help scientists and managers develop, interpret, and apply statistical models
The Journal of Wildlife Management © 2007 Wiley