World Library  


Add to Book Shelf
Flag as Inappropriate
Email this Book

Plotting Partial Correlation and Regression in Ecological Studies : Volume 8, Issue 1 (04/06/2008)

By Moya-laraño, J.

Click here to view

Book Id: WPLBN0004023399
Format Type: PDF Article :
File Size: Pages 12
Reproduction Date: 2015

Title: Plotting Partial Correlation and Regression in Ecological Studies : Volume 8, Issue 1 (04/06/2008)  
Author: Moya-laraño, J.
Volume: Vol. 8, Issue 1
Language: English
Subject: Science, Ecology
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2008
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

APA MLA Chicago

Moya-Laraño, J., & Corcobado, G. (2008). Plotting Partial Correlation and Regression in Ecological Studies : Volume 8, Issue 1 (04/06/2008). Retrieved from http://www.ebooklibrary.org/


Description
Description: Depto. de Ecología Funcional y Evolutiva, Estación Experimental de Zonas Áridas, CSIC, General Segura, 1, Almería, 04001 Almería, Spain. Multiple regression, the General linear model (GLM) and the Generalized linear model (GLZ) are widely used in ecology. The widespread use of graphs that include fitted regression lines to document patterns in simple linear regression can be easily extended to these multivariate techniques in plots that show the partial relationship of the dependent variable with each independent variable. However, the latter procedure is not nearly as widely used in ecological studies. In fact, a brief review of the recent ecological literature showed that in ca. 20% of the papers the results of multiple regression are displayed by plotting the dependent variable against the raw values of the independent variable. This latter procedure may be misleading because the value of the partial slope may change in magnitude and even in sign relative to the slope obtained in simple least-squares regression. Plots of partial relationships should be used in these situations. Using numerical simulations and real data we show how displaying plots of partial relationships may also be useful for: 1) visualizing the true scatter of points around the partial regression line, and 2) identifying influential observations and non-linear patterns more efficiently than using plots of residuals vs. fitted values. With the aim to help in the assessment of data quality, we show how partial residual plots (residuals from overall model + predicted values from the explanatory variable vs. the explanatory variable) should only be used in restricted situations, and how partial regression plots (residuals of Y on the remaining explanatory variables vs. residuals of the target explanatory variable on the remaining explanatory variables) should be the ones displayed in publications because they accurately reflect the scatter of partial correlations. Similarly, these partial plots can be applied to visualize the effect of continuous variables in GLM and GLZ for normal distributions and identity link functions.

Summary
Plotting partial correlation and regression in ecological studies


 

Click To View

Additional Books


  • The Scientific monthly (by )
  • Bulletin - United States National Museum Volume: no. 284 1968 (by )
  • The Philippine Journal of Science Volume: v. 7 pt. D 1912 (by )
  • Comparison of Seawifs and Modis Time Ser... (by )
  • Comparing Historical and Modern Methods ... (by )
  • Stray Leaves from the Book of Nature (by )
  • Kungl. Svenska Vetenskapsakademiens Hand... Volume: ser.1b, 1825 (by )
  • Discours De La Méthode Pour Bien Conduir... (by )
  • Jahresbericht Der Schlesischen Gesellsch... Volume: 30. (1852) (by )
  • Regime Changes in Global Sea Surface Sal... (by )
  • Science (by )
  • The proceedings of the Iowa Academy of S... (by )
Scroll Left
Scroll Right

 



Copyright © World Library Foundation. All rights reserved. eBooks from World eBook Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.