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Ordinal response regression models in ecology
by
Harrell, Frank E.
, Guisan, Antoine
in
Coefficients
/ Datasets
/ Ecological modeling
/ Ecology
/ geographic information systems
/ GLM
/ Logistics
/ logit analysis
/ Modeling
/ Ordinal outcome
/ Plants
/ prediction
/ Predictive distribution modeling
/ Ratios
/ Regression analysis
/ Statistics
/ Stereotypes
2000
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Ordinal response regression models in ecology
by
Harrell, Frank E.
, Guisan, Antoine
in
Coefficients
/ Datasets
/ Ecological modeling
/ Ecology
/ geographic information systems
/ GLM
/ Logistics
/ logit analysis
/ Modeling
/ Ordinal outcome
/ Plants
/ prediction
/ Predictive distribution modeling
/ Ratios
/ Regression analysis
/ Statistics
/ Stereotypes
2000
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Do you wish to request the book?
Ordinal response regression models in ecology
by
Harrell, Frank E.
, Guisan, Antoine
in
Coefficients
/ Datasets
/ Ecological modeling
/ Ecology
/ geographic information systems
/ GLM
/ Logistics
/ logit analysis
/ Modeling
/ Ordinal outcome
/ Plants
/ prediction
/ Predictive distribution modeling
/ Ratios
/ Regression analysis
/ Statistics
/ Stereotypes
2000
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Journal Article
Ordinal response regression models in ecology
2000
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Overview
Although ordinal data are not rare in ecology, ecological studies have, until now, seriously neglected the use of specific ordinal regression models. Here, we present three models – the Proportional Odds, the Continuation Ratio and the Stereotype models – that can be successfully applied to ordinal data. Their differences and respective fields of application are discussed. Finally, as an example of application, PO models are used to predict spatial abundance of plant species in a Geographical Information System. It shows that ordinal models give as good a result as binary logistic models for predicting presence‐absence, but are additionally able to predict abundance satisfactorily.
Publisher
Blackwell Publishing Ltd,Opulus Press
Subject
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