private void CalculatePairwiseTest(string groupName)
{
var columnNames = stringConvertibleMatrixView.Content.ColumnNames.ToList();
int colIndex = columnNames.IndexOf(groupName);
columnNames = columnNames.Where(x => x != groupName).ToList();
double[][] newData = FilterDataForPairwiseTest(colIndex);
var rowNames = new[] { "p-Value of Mann-Whitney U", "Adjusted p-Value of Mann-Whitney U",
"p-Value of T-Test", "Adjusted p-Value of T-Test", "Cohen's d", "Hedges' g" };
DoubleMatrix pValsMatrix = new DoubleMatrix(rowNames.Length, columnNames.Count());
pValsMatrix.ColumnNames = columnNames;
pValsMatrix.RowNames = rowNames;
double mwuBothTails;
double tTestBothTails;
double[] mwuPValues = new double[newData.Length];
double[] tTestPValues = new double[newData.Length];
bool[] decision = null;
double[] adjustedMwuPValues = null;
double[] adjustedTtestPValues = null;
int cnt = 0;
for (int i = 0; i < newData.Length; i++)
{
mwuBothTails = PairwiseTest.MannWhitneyUTest(data[colIndex], newData[i]);
tTestBothTails = PairwiseTest.TTest(data[colIndex], newData[i]);
mwuPValues[i] = mwuBothTails;
tTestPValues[i] = tTestBothTails;
if (mwuBothTails > significanceLevel)
{
cnt++;
}
}
adjustedMwuPValues = BonferroniHolm.Calculate(significanceLevel, mwuPValues, out decision);
adjustedTtestPValues = BonferroniHolm.Calculate(significanceLevel, tTestPValues, out decision);
for (int i = 0; i < newData.Length; i++)
{
pValsMatrix[0, i] = mwuPValues[i];
pValsMatrix[1, i] = adjustedMwuPValues[i];
pValsMatrix[2, i] = tTestPValues[i];
pValsMatrix[3, i] = adjustedTtestPValues[i];
pValsMatrix[4, i] = SampleSizeDetermination.CalculateCohensD(data[colIndex], newData[i]);
pValsMatrix[5, i] = SampleSizeDetermination.CalculateHedgesG(data[colIndex], newData[i]);
}
Invoke(new Action(() => {
pairwiseStringConvertibleMatrixView.Content = pValsMatrix;
pairwiseStringConvertibleMatrixView.DataGridView.AutoResizeColumns(DataGridViewAutoSizeColumnsMode.AllCells);
}));
ShowPairwiseResult(cnt);
}
public void HedgesGTest2()
{
//compared to R effsize package/cohen.d(..,hedges.correction=TRUE)
var result = SampleSizeDetermination.CalculateHedgesG(x, z);
Assert.AreEqual(1.507722, Math.Round(result, 6));
}
public void HedgesGTest1()
{
//compared to R effsize package/cohen.d(..,hedges.correction=TRUE)
var result = SampleSizeDetermination.CalculateHedgesG(x, y);
Assert.AreEqual(0.1986369, Math.Round(result, 7));
}
public void CohensdTest2()
{
//compared to R lsr package/cohenD(..)
var result = SampleSizeDetermination.CalculateCohensD(x, z);
Assert.AreEqual(1.57424, Math.Round(result, 5));
}
public void CohensdTest1()
{
//compared to R lsr package/cohenD(..)
var result = SampleSizeDetermination.CalculateCohensD(x, y);
Assert.AreEqual(0.2074003, Math.Round(result, 7));
}
private void AddSampleSizeText()
{
sampleSizeTextBox.Text = string.Empty;
var usableRuns = Content.Where(r => r.Visible).ToList();
if (!yAxisComboBox.DroppedDown)
{
yAxisValue = (string)yAxisComboBox.SelectedItem;
}
List <double?> yValue = usableRuns.Select(x => GetValue(x, yAxisValue)).ToList();
if (yValue.Any(x => !x.HasValue))
{
return;
}
double estimatedSampleSize = SampleSizeDetermination.DetermineSampleSizeByEstimatingMean(yValue.Select(x => x.Value).ToArray());
sampleSizeTextBox.Text = estimatedSampleSize.ToString();
}
