public double mcdonaldOmega() {
double omega = 0.0;
double sumLambda = 0.0, sumLambda2 = 0.0;
double sumErrorVar = 0.0;
double[] fl = model.getFactorLoading();
double[] er = model.getErrorVariance();
for (int i = 0; i < nItems; i++) {
sumLambda += fl[i];
sumErrorVar += er[i];
}
sumLambda2 = Math.pow(sumLambda, 2);
omega = sumLambda2 / (sumLambda2 + sumErrorVar);
return omega;
}
public AbstractConfirmatoryFactorAnalysisEstimator(
ConfirmatoryFactorAnalysisModel model, RealMatrix varcov, double numberOfExaminees) {
this.model = model;
this.varcov = varcov;
this.numberOfExaminees = numberOfExaminees;
this.nItems = model.getNumberOfItems();
LUDecomposition CVLUD = new LUDecomposition(varcov);
VCinv = CVLUD.getSolver().getInverse();
}
@Override
public String toString() {
StringBuilder sb = new StringBuilder();
Formatter f = new Formatter(sb);
double[] fl = model.getFactorLoading();
double[] er = model.getErrorVariance();
for (int i = 0; i < nItems; i++) {
f.format("% .4f", fl[i]);
f.format("%5s", "");
f.format("% .4f", er[i]);
f.format("%n");
}
f.format("%10s", "McDonald's Omega = ");
f.format("%8.4f", mcdonaldOmega());
f.format("%n");
f.format("%10s", "GFI = ");
f.format("%8.4f", gfi());
f.format("%n");
f.format("%10s", "AGFI = ");
f.format("%8.4f", agfi());
f.format("%n");
f.format("%10s", "RMSEA = ");
f.format("%8.4f", rmsea());
f.format("%n");
f.format("%10s", "RMSR = ");
f.format("%8.4f", Math.sqrt(meanSquaredResidual()));
f.format("%n");
f.format("%10s", "BIC = ");
f.format("%8.4f", Math.sqrt(bic()));
f.format("%n");
f.format("%10s", "X^2 = ");
f.format("%8.4f", chisquare());
f.format("%n");
f.format("%10s", "df = ");
f.format("%8.4f", degreesOfFreedom());
f.format("%n");
f.format("%10s", "p = ");
f.format("%8.4f", pvalue());
f.format("%n");
return f.toString();
}
public String printEstimates(ArrayList<VariableInfo> items) {
StringBuilder sb = new StringBuilder();
Formatter f = new Formatter(sb);
double[] fl = model.getFactorLoading();
double[] er = model.getErrorVariance();
// f.format("%50s", " CONFIRMATORY FACTOR ANALYSIS RESULTS ");
f.format("%n");
f.format("%-50s", model.getName());
f.format("%n");
f.format("%50s", "==================================================");
f.format("%n");
f.format("%10s", " ");
f.format("%5s", "");
f.format("%10s", "Factor ");
f.format("%5s", "");
f.format("%10s", " Error");
f.format("%n");
f.format("%10s", " Item");
f.format("%5s", "");
f.format("%10s", "Loading");
f.format("%5s", "");
f.format("%10s", "Variance");
f.format("%n");
f.format("%50s", "--------------------------------------------------");
f.format("%n");
for (int i = 0; i < items.size(); i++) {
f.format("%10s", items.get(i));
f.format("%5s", "");
f.format("% 10.4f", fl[i]);
f.format("%5s", "");
f.format("% 10.4f", er[i]);
f.format("%n");
}
f.format("%50s", "--------------------------------------------------");
f.format("%n");
return f.toString();
}
public double degreesOfFreedom() {
double ni = Double.valueOf(nItems).doubleValue();
double m = (ni * (ni + 1.0)) / 2.0;
double df = m - model.getNumberOfParameters();
return df;
}
public double bic() {
double b = chisquare() + model.getNumberOfParameters() * Math.log(numberOfExaminees) * nItems;
return b;
}
