@Override
public final void compute() {
String testType;
if (tail.getTextString().equals("<")) {
testType = "left";
} else if (tail.getTextString().equals(">")) {
testType = "right";
} else if (StringUtil.isNotEqual(tail.getTextString())) {
testType = "two";
} else {
result.setUndefined();
return;
}
double n1 = n.getDouble();
double phat1 = proportion.getDouble();
double n2 = n_2.getDouble();
double phat2 = proportion2.getDouble();
double x1 = phat1 * n1;
double x2 = phat2 * n2;
double phatTotal = (x1 + x2) / (n1 + n2);
se = Math.sqrt(phatTotal * (1 - phatTotal) * (1 / n1 + 1 / n2));
double testStatistic = (phat1 - phat2) / se;
NormalDistributionImpl normalDist = new NormalDistributionImpl(0, 1);
double P = 0;
try {
P = normalDist.cumulativeProbability(testStatistic);
} catch (Exception e) {
result.setUndefined();
return;
}
if ("right".equals(testType)) {
P = 1 - P;
} else if ("two".equals(testType)) {
if (testStatistic < 0) {
P = 2 * P;
} else {
P = 2 * (1 - P);
}
}
// put these results into the output list
result.clear();
result.addNumber(P, null);
result.addNumber(testStatistic, null);
}
private void calculateZValues(int n) {
zValues = new double[n];
NormalDistributionImpl normalDist = new NormalDistributionImpl(0, 1);
double x;
try {
x = 1 - Math.pow(0.5, 1.0 / n);
zValues[0] = normalDist.inverseCumulativeProbability(x);
for (int i = 2; i < n; i++) {
x = (i - 0.3175) / (n + 0.365);
zValues[i - 1] = normalDist.inverseCumulativeProbability(x);
}
x = Math.pow(0.5, 1.0 / n);
zValues[n - 1] = normalDist.inverseCumulativeProbability(x);
} catch (MathException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
