Hello,

I have conducted an SEM in which the resultant standardized path coefficients are much higher than would be expected from the raw correlation matrix. To explore further, I stripped the model down to a simple bivariate relationship between two variables (NDVI, and species richness), where it's my understanding that the SEM's standardized path coefficient should equal the correlation coefficient.

The datafile can be downloaded at http://labs.bio.unc.edu/Hurlbert/pubs/NDVI_lep_data.csv
The model specification file can be downloaded at http://labs.bio.unc.edu/Hurlbert/pubs/SEM_NDVI_AllS_model.txt
and is simply:

NDVI -> All.S, n2S, NA
All.S -> All.S, S2S, NA
NDVI <-> NDVI, n2n, 1

df = read.csv('NDVI_lep_data.csv',header=T)
cor(df[,c('NDVI','All.S')])

yields:


           NDVI     All.S

NDVI  1.0000000 0.4156191

All.S 0.4156191 1.0000000

But, conducting an SEM yields:

sem.mod = specifyModel('SEM_NDVI_AllS_model.txt')
sem.mod.cov = rawMoments(~ NDVI + All.S, data = df)
sem.mod.cov = sem.mod.cov[-1,-1]
sem.mod.cov


            NDVI     All.S

NDVI   0.7820657  13.53573

All.S 13.5357259 245.71360

sem1 = sem(sem.mod, sem.mod.cov, N=29)
stdCoef(sem1)


n2S n2S    0.97643950  All.S <--- NDVI

n2n n2n    1.00000000   NDVI <--> NDVI

s2S s2S    0.04656591 All.S <--> All.S

I am using version 3.0 of sem on R-14.0.

Thanks for any insight anyone can provide.

Allen Hurlbert, Ph.D.
Department of Biology
University of North Carolina
Chapel Hill, NC 27599-3280
Tel: 919.843.9930
Wilson Hall 331



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