Multicollinearity of explanatory variables often threatens statistical interpretation of ecological data analysis in biodiversity studies. Using litter ants as an example,the impact of multicollinearity on ecological multiple regression and complications arsing from collinearity is explained.We list the various statistical techniques available for enhancing the reliability and interpretation of ecological multiple regressions in the presence of multicollinearity
Simulated data are used to test the impact of aggregation and of multicollinearity on the results of...
Confusion exists over the proper statistical methodology to use in analyzing the effect of treatment...
The most common statistical pitfalls in ecological research are those associated with data explorati...
For decades multivariate analysis has been recognised as being appropriate for the analysis and desc...
International audienceDirect gradient analyses in spatial genetics provide unique opportunities to d...
Although analytical methods in statistics have all along been generic and evolutionary in the first...
Direct gradient analyses in spatial genetics provide unique opportunities to describe the inherent c...
Direct gradient analyses in spatial genetics provide unique opportunities to describe the inherent c...
Diversity indices, particularly the Shannon-Wiener index, have extensively been used in analyzing pa...
Ecological problems often require multivariate analyses. Ever since Bray and Curtis (1957) drew an ...
Although analytical methods in statistics have all along been generic and evolutionary in the first...
Multivariate regression trees (MRT) are a new statistical technique that can be used to explore, des...
Collinearity refers to the non independence of predictor variables, usually in a regression-type ana...
In the mid 1980s attempts were made to devise a form of multivariate analysis which measured the ten...
Contemporary biological assemblage composition and biodiversity are often shaped by a range of natur...
Simulated data are used to test the impact of aggregation and of multicollinearity on the results of...
Confusion exists over the proper statistical methodology to use in analyzing the effect of treatment...
The most common statistical pitfalls in ecological research are those associated with data explorati...
For decades multivariate analysis has been recognised as being appropriate for the analysis and desc...
International audienceDirect gradient analyses in spatial genetics provide unique opportunities to d...
Although analytical methods in statistics have all along been generic and evolutionary in the first...
Direct gradient analyses in spatial genetics provide unique opportunities to describe the inherent c...
Direct gradient analyses in spatial genetics provide unique opportunities to describe the inherent c...
Diversity indices, particularly the Shannon-Wiener index, have extensively been used in analyzing pa...
Ecological problems often require multivariate analyses. Ever since Bray and Curtis (1957) drew an ...
Although analytical methods in statistics have all along been generic and evolutionary in the first...
Multivariate regression trees (MRT) are a new statistical technique that can be used to explore, des...
Collinearity refers to the non independence of predictor variables, usually in a regression-type ana...
In the mid 1980s attempts were made to devise a form of multivariate analysis which measured the ten...
Contemporary biological assemblage composition and biodiversity are often shaped by a range of natur...
Simulated data are used to test the impact of aggregation and of multicollinearity on the results of...
Confusion exists over the proper statistical methodology to use in analyzing the effect of treatment...
The most common statistical pitfalls in ecological research are those associated with data explorati...