Michael, As a general rule of thumb (I believe this is in Jim Grace's book, if not others) one should use 10-20 observations per variable. If you have 5 variables, and 18 observations, you should probably be a bit suspect of your results. That said, if some of your paths are indeed non-significant, well, they might be! Have you tried an alternate model with those paths set to 0? You can them compare the two models in a variety of ways (LR tests, compare BIC values, etc).
-Jarrett Michael Rennie-2 wrote: > > > Hi there, > > Quick question about the output from the sem() function in the library > of the same name. > > If I am getting probabilities >0.05 for some of my estimates of path > coefficients, I'm assuming the interpretation here is that the > coefficient is not significantly different from zero, correct? In that > case, might it make sense that I should disregard path coefficients > between variables where the probability is greater than 0.05? In which > case, would it make further sense to remove those particular links from > the specify.model() command and re-run the analysis, excluding those > rows which lacked significance in the previous attempt? > > Given that in just about every other example I've been able to dig up > where this method is employed (including other datasets I am working > with), the probabilities of the path coefficients are almost always well > below 0.05, it makes me suspect that what I am observing may simply > result from the fact that I'm trying to fit a path analysis among 5 > variables (4 predictors, 1 criterion) based on only 18 observations, > admittedly a small sample size and perhaps an overly ambitious approach > to analyzing so few data. > > Last, I'm convinced that I'm using the code correctly as I was able to > successfully reproduce an example in Quinn and Keough (2002) before I > turned the code onto my own data. > > -- View this message in context: http://www.nabble.com/interpreting-significance-of-path-coefficients-from-sem%28%29-output-tp17096769p17096869.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
