Access the full text.
Sign up today, get DeepDyve free for 14 days.
B. Peterson, F. Harrell (1990)
Partial Proportional Odds Models for Ordinal Response VariablesApplied statistics, 39
E. Läärä, J. Matthews (1985)
The equivalence of two models for ordinal dataBiometrika, 72
J. Landwehr, D. Pregibon, A. Shoemaker (1984)
Graphical Methods for Assessing Logistic Regression ModelsJournal of the American Statistical Association, 79
S. Greenland (1994)
Alternative models for ordinal logistic regression.Statistics in medicine, 13 16
B. Efron, Gail Gong (1983)
A Leisurely Look at the Bootstrap, the Jackknife, and
R. Monserud, R. Leemans (1992)
Comparing global vegetation maps with the Kappa statisticEcological Modelling, 62
Strother Walker, D. Duncan (1967)
Estimation of the probability of an event as a function of several independent variables.Biometrika, 54 1
A. Nicholls (1989)
How to make biological surveys go further with generalised linear modelsBiological Conservation, 50
R. Howell, R. Zeller, E. Carmines (1980)
Measurement in the social sciences
Jae-on Kim (1971)
Predictive Measures of Ordinal AssociationAmerican Journal of Sociology, 76
Ben Armstrong, Margaret Sloan (1989)
Ordinal regression models for epidemiologic data.American journal of epidemiology, 129 1
S. Greenland (1985)
An Application of Logistic Models to the Analysis of Ordinal ResponsesMarch 1985
F. Harrell, P. Margolis, S. Gove, K. Mason, E. Mulholland, D. Lehmann, L. Muhe, S. Gatchalian, H. Eichenwald (1998)
Development of a clinical prediction model for an ordinal outcome: the World Health Organization Multicentre Study of Clinical Signs and Etiological agents of Pneumonia, Sepsis and Meningitis in Young Infants. WHO/ARI Young Infant Multicentre Study Group.Statistics in medicine, 17 8
B. Efron, R. Tibshirani (1995)
An Introduction to the Bootstrap
Greenland Greenland (1985)
An application of logistic models to the analysis of ordinal responsesBiometr. J., 2
M. Hill, R. Jongman, C. Braak, O. Tongeren (1987)
Data analysis in community and landscape ecologyJournal of Animal Science
L. Goodman, W. Kruskal (1979)
Measures of association for cross classifications
Harrell Harrell, Lee Lee, Mark Mark (1996)
Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errorsStat. Med., 15
J. Ashford (1959)
An Approach to the Analysis of Data for Semi-Quantal Responses in Biological AssayBiometrics, 15
A. Schlüssel, J. Theurillat (1998)
Phenology of Rhododendron ferrugineum L. in two altitudinal gradients of the Valaisian Alps (Switzerland), 29
Maarel Maarel (1979)
Transformation of cover‐abundance values in phytosociology and its effects on community similarityVegetatio, 39
Efron Efron, Gong Gong (1983)
A leisurely look at the bootstrap, the jacknife, and cross‐validationAm. Stat., 37
Richard Gonzalez, Thomas Nelson (1996)
Measuring ordinal association in situations that contain tied scores.Psychological bulletin, 119 1
T. Wilson (1974)
Measures of Association for Bivariate Ordinal Hypotheses
J. Barkman, H. Doing, S. Segal (1964)
KRITISCHE BEMERKUNGEN UND VORSCHLÄGE ZUR QUANTITATIVEN VEGETATIONSANALYSEPlant Biology, 13
P. McCullagh (1980)
Regression Models for Ordinal DataJournal of the royal statistical society series b-methodological, 42
Barkman Barkman, Doing Doing, Segal Segal (1964)
Kritische Bemerkungen und Vorschläge zur quantitativen VegetationsanalyseActa Bot. Neerl., 13
N. Nagelkerke (1991)
A note on a general definition of the coefficient of determinationBiometrika, 78
A. Guisan, J. Theurillat, F. Kienast (1998)
Predicting the potential distribution of plant species in an alpine environmentJournal of Vegetation Science, 9
Guisan Guisan, Weiss Weiss, Weiss Weiss (1999)
GLM versus CCA spatial modeling of plant species distributionPlant Ecol., 143
O. Schabenberger (1995)
The use of ordinal response methodology in forestryForest Science, 41
Harrell Harrell, Margolis Margolis, Gove Gove, Mason Mason, Mulholland Mulholland, Lehmann Lehmann, Muhe Muhe, Gatchalian Gatchalian, Eichenwald Eichenwald (1998)
Development of clinical prediction model for an ordinal outcomeStat. Med., 17
O. Williams, J. Grizzle (1972)
Analysis of Contingency Tables Having Ordered Response CategoriesJournal of the American Statistical Association, 67
Anderson Anderson (1984)
Regression and ordered categorical variables (with discussion)J. R. Stat. Soc., B46
Guisan Guisan, Theurillat Theurillat, Kienast Kienast (1998)
Using static modeling to predict potential distributions of species in an alpine environmentJ. Veg. Sci., 9
E. Snell (1964)
A Scaling Procedure for Ordered Categorical DataBiometrics, 20
R. Somers (1962)
A new asymmetric measure of association for ordinal variables.American Sociological Review, 27
Jacob Cohen (1960)
A Coefficient of Agreement for Nominal ScalesEducational and Psychological Measurement, 20
Abstract. 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.
Journal of Vegetation Science – Wiley
Published: Oct 1, 2000
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.