You are not currently logged in.
Access your personal account or get JSTOR access through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Testing Evolutionary and Ecological Hypotheses Using Path Analysis and Structural Equation Modelling
R. J. Mitchell
Vol. 6, No. 2 (1992), pp. 123-129
Published by: British Ecological Society
Stable URL: http://www.jstor.org/stable/2389745
Page Count: 7
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
The use of path analysis has grown rapidly in recent years, yet few studies employ recent advances in the field of structural equation modelling (SEM). Here I illustrate the capabilities of SEM for path analyses, using data from a study of hummingbird pollination. The main drawback to conventional path analysis is that the overall agreement between the path diagram (or `model') and the data is not quantified; this also means that there is no clear way to directly compare competing models of the same system. One of the major advantages of SEM is that it can test the descriptive ability of different models, thus allowing them to be compared. When unmeasured latent variables are required (e.g. to circumvent problems with multi-collinearity to include estimates of measurement error, or to represent general `factors' such as size), SEM can directly incorporate them as well. Furthermore, SEM provides `modification indices' that indicate areas where the fit of a given model is especially poor, and therefore point to further observations or models that might adequately describe the data. Beyond these advantages, SEM also provides all the information provided by standard path analysis, including path coefficients, measures of explained variance, and total effects. These capabilities make structural equation modelling a powerful tool with which to apply path analysis to observational data sets in ecology and evolution.
Functional Ecology © 1992 British Ecological Society