I am trying to use sem to measure effective connectivity among four  
brain regions.  I have pasted the code that I am trying to run since  
that seems easier than trying to come up with another example.

The input data is time series data taken from SPM; they are each  
1x121 columns of numbers.  I get the error either when I source the  
whole code, or if I enter it line by line when I go to get the summary.

Thanks,

Suzanne

library(sem)

# Load the region timecourses.

lsma1 <- read.table("/Users/witt/parkinsons/rmrkm010905/R_files/ 
010905_lcomf_LSMA.dat")
rsma1 <- read.table("/Users/witt/parkinsons/rmrkm010905/R_files/ 
010905_lcomf_RSMA.dat")
lmc1 <- read.table("/Users/witt/parkinsons/rmrkm010905/R_files/ 
010905_lcomf_LM1.dat")
rmc1 <- read.table("/Users/witt/parkinsons/rmrkm010905/R_files/ 
010905_lcomf_RM1.dat")

# Combine all the timecourses from each session into a single data  
frame and name the columns appropriately.

lcomf <- cbind(lsma1, rsma1, lmc1, rmc1)
names(lcomf) <- c("LSMA", "RSMA", "LM1", "RM1")

# Type this at the command line to see a summary of your data

str(lcomf)

# Set up the structural equation model.

p.ram <<- matrix(c( 'LM1 -> LSMA', 'LM1 -> LSMA', NA,
             'LSMA -> RSMA', 'LSMA -> RSMA', NA,
             'RSMA -> RM1', 'RSMA -> RM1', NA,
             'LSMA <-> LSMA', 'LSMA <-> LSMA', NA,
             'RSMA <-> RSMA', 'RSMA <-> RSMA', NA,
             'RM1 <-> RM1', 'RM1 <-> RM1', NA),
                 ncol = 3, byrow = TRUE)

# Tell which variables are exogenous ('fixed').

p.fixed <- c('LM1')

# Do the fitting for session 1.

C <- cor(lcomf)
nt <- dim(lcomf)[1]
#attach(lcomf)
lcomf.results <- sem(p.ram, C, nt, obs.variables = rownames(C),  
fixed.x = p.fixed)

# Check out the results using the summary function

summary(lcomf.results)


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