I am a PhD Student in forest ecology and, these days, I'm having a lot of fun analyzing my data. My objective is to evaluate the effect of many factors on the diameter growth of black spruces, including stand age, competition and spruce budworm defoliation. Competition pressure is estimated with the relative density, which is the observed density (stems per ha) divided by the maximum potential density, according to the stand density management diagram (developed by Newton and Weetman 1993). My goal is to quantify the importance of each factor on tree growth. However most of these "independent" variables are in fact correlated to each other . For instance, relative density is strongly correlated with stand age, since the competition stress increases with tree size. The occurence of spruce budworm outbreaks is also correlated to stand age, since outbreaks occur during specific periods on large territories and most of my stands have the same age. This multicorrelation, or colinearity, seems to be a major obstacle to the use of multiple regression (cf Neter, Wasserman & Kutner 1990). When collinearity is important, the estimation of the partial regression coefficients seems to be hazardous. On the other hand, in their classical handbook, Sokal & Rohlf (1981) suggest path analysis as a powerful tool to investigate complex networks of inter-correlated variables. This approach is based on the determination of causality relationships; the strengh of these relations is estimated with multiple regressions. However, Sokal & Rohlf seemed not to bother with colinearity... Since I obviously do not fully understand the nuts and bolts of multiple regression and path analysis, I need help to answer these questions: (1) Is path analysis a relevant approach to solve my theorical problem (i.e. evaluate the importance of competition on growth)? (2) If it is relevant, how should I manage the colinearity problem? (3) If path analysis is not adequate, are there possible alternatives? I hope the description of my problem is sufficient. Any comment from my colleagues forumites will be welcome! HELP ME! I'M (ALMOST) DESPERATE!!! Jean-Martin Lussier Universite du Quebec a Chicoutimi E-Mail: jmlussie@uqac.uquebec.ca
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