# NOT RUN {
# }
# NOT RUN {
library(lavaan)
HW.model <- ' visual =~ x1 + c1*x2 + x3
textual =~ x4 + c1*x5 + x6
speed =~ x7 + x8 + x9 '
fit <- cfa(HW.model, data=HolzingerSwineford1939, group="school", meanstructure=TRUE)
# Copy the summary of the lavaan object
clipboard(fit)
# Copy the modification indices and the model fit from the miPowerFit function
clipboard(fit, "mifit")
# Copy the parameter estimates
clipboard(fit, "coef")
# Copy the standard errors
clipboard(fit, "se")
# Copy the sample statistics
clipboard(fit, "samp")
# Copy the fit measures
clipboard(fit, "fit")
# Save the summary of the lavaan object
saveFile(fit, "out.txt")
# Save the modification indices and the model fit from the miPowerFit function
saveFile(fit, "out.txt", "mifit")
# Save the parameter estimates
saveFile(fit, "out.txt", "coef")
# Save the standard errors
saveFile(fit, "out.txt", "se")
# Save the sample statistics
saveFile(fit, "out.txt", "samp")
# Save the fit measures
saveFile(fit, "out.txt", "fit")
# }
# NOT RUN {
# }
Run the code above in your browser using DataLab