Dear Allen, There's enough wrong here that it's easier for me just to fix it.
First, if you're going to fit to a raw moment matrix, then (unless you want to do regression through the origin), you'll need to specify an intercept: ------- snip --------- > df <- read.csv('NDVI_lep_data.csv', header=TRUE) > sem.mod.raw <- rawMoments(~ NDVI + All.S, data = df) > sem.mod.raw Raw Moments (Intercept) NDVI All.S (Intercept) 1.000000 0.8841920 15.28161 NDVI 0.884192 0.7820657 13.53573 All.S 15.281609 13.5357259 245.71360 N = 29 > > sem.mod <- specifyModel() 1: NDVI -> All.S, n2S, NA 2: (Intercept) -> All.S, intercept, NA 3: All.S <-> All.S, s2S, NA 4: Read 3 records > sem.mod Path Parameter 1 NDVI -> All.S n2S 2 (Intercept) -> All.S intercept 3 All.S <-> All.S s2S > sem1 <- sem(sem.mod, sem.mod.raw, N=29, raw=TRUE, + fixed.x=c("(Intercept)", "NDVI")) > summary(sem1) Model fit to raw moment matrix. Model Chisquare = 1.0174e-11 Df = 0 Pr(>Chisq) = NA AIC = 6 AICc = 0.96 BIC = 10.102 CAIC = 1.0174e-11 Normalized Residuals Min. 1st Qu. Median Mean 3rd Qu. Max. -7.72e-13 -3.99e-13 -3.97e-13 -2.63e-13 0.00e+00 0.00e+00 Parameter Estimates Estimate Std Error z value Pr(>|z|) n2S 88.262 35.8674 2.4608 0.01386342 All.S <--- NDVI intercept -62.759 31.7191 -1.9786 0.04786344 All.S <--- (Intercept) s2S 10.081 2.6474 3.8079 0.00014016 All.S <--> All.S Iterations = 0 > summary(lm(All.S ~ NDVI, data=df)) # check Call: lm(formula = All.S ~ NDVI, data = df) Residuals: Min 1Q Median 3Q Max -5.474 -2.009 -1.337 3.978 5.298 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -62.76 32.87 -1.909 0.0669 . NDVI 88.26 37.17 2.374 0.0249 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 3.291 on 27 degrees of freedom Multiple R-squared: 0.1727, Adjusted R-squared: 0.1421 F-statistic: 5.638 on 1 and 27 DF, p-value: 0.02494 ----------- snip ----------------- Here are other, more convenient, ways of getting the same thing (with output not shown): ----------- snip ----------------- summary(sem(sem.mod, data=df, raw=TRUE, formula= ~ NDVI + All.S, fixed.x=c("(Intercept)", "NDVI"))) sem.mod <- specifyEquations() All.S = intercept*(Intercept) + n2S*NDVI summary(sem(sem.mod, data=df, raw=TRUE, formula= ~ NDVI + All.S, fixed.x=c("(Intercept)", "NDVI"))) ----------- snip ----------------- To get standardized coefficients, however, you should fit to a covariance matrix, rather than a raw moment matrix. As it turns out, this won't work currently for your model specified as I've done it above, because the model contains only one explicit parameter. This is unusual, which is probably why the problem didn't surface previously. I've fixed specifyModel() so that it will work in this situation, which then produces the following: ----------- snip ----------------- > sem.mod.noint <- specifyModel() 1: NDVI -> All.S, n2S 2: Read 1 record NOTE: adding 1 variances to the model > sem2 <- sem(sem.mod.noint, data=df, formula= ~ NDVI + All.S, + fixed.x="NDVI") > summary(sem2) Model Chisquare = 0 Df = 0 Pr(>Chisq) = NA Chisquare (null model) = 5.3098 Df = 1 Goodness-of-fit index = 1 AIC = 4 AICc = 0.46154 BIC = 6.7346 CAIC = 0 Normalized Residuals Min. 1st Qu. Median Mean 3rd Qu. Max. 0 0 0 0 0 0 Parameter Estimates Estimate Std Error z value Pr(>|z|) n2S 88.262 36.5022 2.4180 0.01560679 All.S <--- NDVI V[All.S] 10.441 2.7905 3.7417 0.00018281 All.S <--> All.S Iterations = 0 > standardizedCoefficients(sem2) Std. Estimate n2S n2S 0.4156191 All.S <--- NDVI V[All.S] V[All.S] 0.8272607 All.S <--> All.S 1.0000000 NDVI <--> NDVI > with(df, cor(NDVI, All.S)) # check [1] 0.4156191 ----------- snip ----------------- I'll fix specifyModel() so that it works for a model with one explicit parameter in the next version of the sem package. In the meantime, you can duplicate what I've done as follows (output not shown): ----------- snip ----------------- sem.mod.noint.2 <- specifyModel() NDVI -> All.S, n2S All.S <-> All.S, err.All.S sem3 <- sem(sem.mod.noint.2, data=df, formula= ~ NDVI + All.S, fixed.x="NDVI") summary(sem3) ----------- snip ----------------- Best, John ------------------------------------------------------- John Fox Senator William McMaster Professor of Social Statistics Department of Sociology McMaster Univeristy Hamilton, Ontario, Canada > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] > On Behalf Of Hurlbert, Allen Hartley > Sent: August-03-12 5:37 PM > To: r-help@r-project.org > Subject: [R] SEM standardized path coefficients > > 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 > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting- > guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.