> # working dir. > > setwd("C:/Users/yenni/testing") > > ################################################# > #File name : cfa3rdgroup1matrix_in.R > ################################################# > > ## DATA > input_file1 <- "group1.txt" > > library(OpenMx) > > #data group1 > flan_3rd <- read.table(file = input_file1, header = FALSE) > flan_3rd <- flan_3rd[c(45:48,50:59,65,66)] > flan_3rd<-flan_3rd[1:1274,] > is.na(flan_3rd)=flan_3rd==999.0000 > manifestVars<-c('V1', 'V2', 'V3', 'V4', 'V5', 'V6', 'V7', 'V8', 'V9', 'V10', 'V11', 'V12', 'V13','V14', 'V15', 'V16') > latentVars<-c("I","E","A") > colnames(flan_3rd)<-manifestVars > dataRaw1<-mxData(observed=flan_3rd, type="raw") > > mx.A <- mxMatrix( + type = "Full", + nrow=19, + ncol=19, + + values = c(0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.004,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.981,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.909,0.000,0.000, + + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.429,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.697,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.457,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.365,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.312,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.778,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.534,0.000, + + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.883, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.046, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.956, + + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000 + ), + free = c(F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, F, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, F, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, F, F, + + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, F, + + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, + + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F + ), + + labels= c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg111", NA, NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg121", NA, NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg131", NA, NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg141", NA, NA, + + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg112", NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg122", NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg132", NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg142", NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg152", NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg162", NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg172", NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg182", NA, + + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg113", + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg123", + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg133", + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Lg143", + + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA + ), + + byrow=TRUE, + #Provide a matrix name that will be used in model fitting + name="A", + ) > > mx.S<-mxMatrix( + type = "Symm", + nrow=19, + ncol=19, + + values = c(0.428,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.464,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.367,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.555,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + + 0.000,0.000,0.000,0.000,0.927,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.553,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.477,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.601,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.888,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.655,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.473,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.802,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.878,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.052,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.798,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.101,0.000,0.000,0.000, + + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.587,0.257,-0.256, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.257,0.435,-0.300, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,-0.256,-0.300,0.512 + ), + free = c(T, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, + F, T, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, + F, F, T, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, + F, F, F, T, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, + + F, F, F, F, T, F, F, F, F, F, F, F, F, F, F, F, F, F, F, + F, F, F, F, F, T, F, F, F, F, F, F, F, F, F, F, F, F, F, + F, F, F, F, F, F, T, F, F, F, F, F, F, F, F, F, F, F, F, + F, F, F, F, F, F, F, T, F, F, F, F, F, F, F, F, F, F, F, + F, F, F, F, F, F, F, F, T, F, F, F, F, F, F, F, F, F, F, + F, F, F, F, F, F, F, F, F, T, F, F, F, F, F, F, F, F, F, + F, F, F, F, F, F, F, F, F, F, T, F, F, F, F, F, F, F, F, + F, F, F, F, F, F, F, F, F, F, F, T, F, F, F, F, F, F, F, + + F, F, F, F, F, F, F, F, F, F, F, F, T, F, F, F, F, F, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, T, F, F, F, F, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, F, F, F, F, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, F, F, F, + + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, T, T, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, T, T, + F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, F, T, T, T + ), + + labels= c("eg111", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, + NA, "eg121", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, + NA, NA, "eg131", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, + NA, NA, NA, "eg141", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, + + NA, NA, NA, NA, "eg112", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, + NA, NA, NA, NA, NA, "eg122", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, + NA, NA, NA, NA, NA, NA, "eg132", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, + NA, NA, NA, NA, NA, NA, NA, "eg142", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, + NA, NA, NA, NA, NA, NA, NA, NA, "eg152", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, "eg162", NA, NA, NA, NA, NA, NA, NA, NA, NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "eg172", NA, NA, NA, NA, NA, NA, NA, NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "eg182", NA, NA, NA, NA, NA, NA, NA, + + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "eg113", NA, NA, NA, NA, NA, NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "eg123", NA, NA, NA, NA, NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "eg133", NA, NA, NA, NA, + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "eg143", NA, NA, NA, + + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "varI", "covIE", "covIA", + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "covIE", "varE", "covEA", + NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "covIA", "covEA", "varA" + + ), + + byrow=TRUE, + #Provide a matrix name that will be used in model fitting + name="S", + ) > > mx.F <- mxMatrix("Full", nrow=16, ncol=19, + values= c(1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + + 0.000,0.000,0.000,0.000,1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000, + + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.000,0.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.000,0.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.000,0.000,0.000,0.000,0.000, + 0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,1.000,0.000,0.000,0.000 + + + ), + free=FALSE, + name="F", + byrow = TRUE + ) > > mx.M<-mxMatrix(type="Full", nrow=1, ncol=19, + free=c(T,T,T,T,T,T,T,T,T,T,T,T,T,T,T,T,F,F,F), + values=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0), + labels=c("mean_g1V1","mean_g1V2","mean_g1V3","mean_g1V4","mean_g1V5","mean_g1V6","mean_g1V7","mean_g1V8","mean_g1V9","mean_g1V10", + "mean_g1V11","mean_g1V12","mean_g1V13","mean_g1V14","mean_g1V15","mean_g1V16",NA,NA,NA), + name="M" ) > > > exp <- mxExpectationRAM("A","S","F","M", dimnames=c(manifestVars, latentVars)) > funML <- mxFitFunctionML() > > Model1_G1 <- mxModel("group1", dataRaw1, mx.A, mx.S, mx.F, mx.M, exp, funML) > > Model1G1Fit <- mxRun(Model1_G1) Running group1 with 51 parameters Warning message: In model 'group1' Optimizer returned a non-zero status code 6. The model does not satisfy the first-order optimality conditions to the required accuracy, and no improved point for the merit function could be found during the final linesearch (Mx status RED) > > Model1G1Fit1 <- mxRun(Model1G1Fit) Running group1 with 51 parameters Warning message: In model 'group1' Optimizer returned a non-zero status code 6. The model does not satisfy the first-order optimality conditions to the required accuracy, and no improved point for the merit function could be found during the final linesearch (Mx status RED) > sumModel1G1Fit1<-summary(Model1G1Fit1) > sumModel1G1Fit1 Summary of group1 The model does not satisfy the first-order optimality conditions to the required accuracy, and no improved point for the merit function could be found during the final linesearch (Mx status RED) free parameters: name matrix row col Estimate Std.Error A 1 Lg121 A 2 17 1.05674510 0.0571941783 ! 2 Lg131 A 3 17 0.87910670 0.0497760656 ! 3 Lg141 A 4 17 0.98272372 0.0540767793 ! 4 Lg122 A 6 18 0.02630098 0.0138320638 ! 5 Lg132 A 7 18 -0.02910870 0.0143396566 ! 6 Lg142 A 8 18 0.10874835 0.0176224398 ! 7 Lg152 A 9 18 1.35718576 0.0284406854 ! 8 Lg162 A 10 18 1.02740630 0.0269488996 ! 9 Lg172 A 11 18 1.56564683 0.0094004330 ! 10 Lg182 A 12 18 1.47820416 0.0287387465 ! 11 Lg123 A 14 19 0.42418951 0.0202790541 ! 12 Lg133 A 15 19 0.91063094 0.0104958038 ! 13 Lg143 A 16 19 0.71029052 0.0373742032 ! 14 eg111 S 1 1 0.64492467 0.0340581277 ! 15 eg121 S 2 2 0.71079754 0.0338806966 ! 16 eg131 S 3 3 0.44536536 0.0239467858 ! 17 eg141 S 4 4 0.50628743 0.0281934090 ! 18 eg112 S 5 5 2.25033238 0.0513201760 ! 19 eg122 S 6 6 1.00836767 0.0417486073 ! 20 eg132 S 7 7 1.12224953 0.0511162288 ! 21 eg142 S 8 8 1.16380905 0.0496665596 ! 22 eg152 S 9 9 0.48348897 0.0081856294 ! 23 eg162 S 10 10 0.55836840 0.0140402245 ! 24 eg172 S 11 11 0.13781977 0.0012388054 ! 25 eg182 S 12 12 0.45528217 0.0074296339 ! 26 eg113 S 13 13 1.19333179 0.0108359797 ! 27 eg123 S 14 14 0.74500918 0.0293717989 ! 28 eg133 S 15 15 0.27137758 0.0055802157 ! 29 eg143 S 16 16 0.74108451 0.0338490270 ! 30 varI S 17 17 0.38897683 0.0291056930 ! 31 covIE S 17 18 0.13938045 0.0093246681 ! 32 varE S 18 18 0.23372488 0.0001544953 ! 33 covIA S 17 19 0.23932744 0.0161879582 ! 34 covEA S 18 19 0.46633822 0.0007906591 ! 35 varA S 19 19 0.60278732 0.0013725573 ! 36 mean_g1V1 M 1 V1 2.38378346 0.0286072583 ! 37 mean_g1V2 M 1 V2 2.39417781 0.0300427393 ! 38 mean_g1V3 M 1 V3 2.21658800 0.0242608840 ! 39 mean_g1V4 M 1 V4 2.19194826 0.0263677960 ! 40 mean_g1V5 M 1 V5 2.71089201 0.0441932020 ! 41 mean_g1V6 M 1 V6 2.84323359 0.0282866246 ! 42 mean_g1V7 M 1 V7 2.76154015 0.0296839550 ! 43 mean_g1V8 M 1 V8 3.30302822 0.0302837321 ! 44 mean_g1V9 M 1 V9 3.01145045 0.0268998562 ! 45 mean_g1V10 M 1 V10 2.71169905 0.0251905120 ! 46 mean_g1V11 M 1 V11 3.00132188 0.0237137340 ! 47 mean_g1V12 M 1 V12 3.04818584 0.0277256473 ! 48 mean_g1V13 M 1 V13 3.05249356 0.0376061937 ! 49 mean_g1V14 M 1 V14 2.74226390 0.0260515382 ! 50 mean_g1V15 M 1 V15 2.99179993 0.0246941773 ! 51 mean_g1V16 M 1 V16 3.01182942 0.0288402948 ! observed statistics: 20384 estimated parameters: 51 degrees of freedom: 20333 fit value ( -2lnL units ): 46075.8 number of observations: 1274 ** Information matrix is not positive definite (not at a candidate optimum). Be suspicious of these results. At minimum, do not trust the standard errors. Information Criteria: | df Penalty | Parameters Penalty | Sample-Size Adjusted AIC: 5409.796 46177.80 NA BIC: -99303.463 46440.44 46278.44 To get additional fit indices, see help(mxRefModels) timestamp: 2017-01-17 09:21:58 Wall clock time (HH:MM:SS.hh): 00:00:07.96 optimizer: SLSQP OpenMx version number: 2.6.9 Need help? See help(mxSummary)