Ejemplo n.º 1
0
  private double paramValue(SemIm im, Parameter parameter) {
    double paramValue = im.getParamValue(parameter);

    if (parameter.getType() == ParamType.VAR) {
      paramValue = Math.sqrt(paramValue);
    }

    return paramValue;
  }
Ejemplo n.º 2
0
  private String compileReport() {
    StringBuilder builder = new StringBuilder();

    builder.append("Datset\tFrom\tTo\tType\tValue\tSE\tT\tP");

    java.util.List<SemEstimator> estimators = wrapper.getMultipleResultList();

    for (int i = 0; i < estimators.size(); i++) {
      SemEstimator estimator = estimators.get(i);

      SemIm estSem = estimator.getEstimatedSem();
      String dataName = estimator.getDataSet().getName();

      for (Parameter parameter : estSem.getFreeParameters()) {
        builder.append("\n");
        builder.append(dataName + "\t");
        builder.append(parameter.getNodeA() + "\t");
        builder.append(parameter.getNodeB() + "\t");
        builder.append(typeString(parameter) + "\t");
        builder.append(asString(paramValue(estSem, parameter)) + "\t");
        /*
         Maximum number of free parameters for which statistics will be
         calculated. (Calculating standard errors is high complexity.) Set this to
         zero to turn  off statistics calculations (which can be problematic
         sometimes).
        */
        int maxFreeParamsForStatistics = 200;
        builder.append(
            asString(estSem.getStandardError(parameter, maxFreeParamsForStatistics)) + "\t");
        builder.append(asString(estSem.getTValue(parameter, maxFreeParamsForStatistics)) + "\t");
        builder.append(asString(estSem.getPValue(parameter, maxFreeParamsForStatistics)) + "\t");
      }

      List<Node> nodes = estSem.getVariableNodes();

      for (int j = 0; j < nodes.size(); j++) {
        Node node = nodes.get(j);

        int n = estSem.getSampleSize();
        int df = n - 1;
        double mean = estSem.getMean(node);
        double stdDev = estSem.getMeanStdDev(node);
        double stdErr = stdDev / Math.sqrt(n);

        double tValue = mean / stdErr;
        double p = 2.0 * (1.0 - ProbUtils.tCdf(Math.abs(tValue), df));

        builder.append("\n");
        builder.append(dataName + "\t");
        builder.append(nodes.get(j) + "\t");
        builder.append(nodes.get(j) + "\t");
        builder.append("Mean" + "\t");
        builder.append(asString(mean) + "\t");
        builder.append(asString(stdErr) + "\t");
        builder.append(asString(tValue) + "\t");
        builder.append(asString(p) + "\t");
      }
    }

    return builder.toString();
  }