public void SaveResult(EffectSizeResult result, string filename)
{
using (var streamWriter = new StreamWriter(filename))
{
streamWriter.WriteLine("Effektstärkeergebnisse vom {0}:", DateTime.Now);
streamWriter.WriteLine();
streamWriter.WriteLine("1. Variable: {0}", _cohensSettings.SelectedFirstVariable);
streamWriter.WriteLine("2. Variable: {0}", _cohensSettings.SelectedSecondVariable);
if (!string.IsNullOrEmpty(_cohensSettings.SelectedFilterVariable))
{
streamWriter.WriteLine("Filtervariable: {0}", _cohensSettings.SelectedFilterVariable);
streamWriter.WriteLine("Filter: {0}", _cohensSettings.Filter);
}
streamWriter.Write("Gleiche Varianzen: ");
streamWriter.WriteLine(_cohensSettings.SameVariances ? "ja" : "nein");
streamWriter.WriteLine();
streamWriter.WriteLine("Cohen's d: {0}", result.Result);
streamWriter.WriteLine("Konfidenzintervall: {0} - {1}", result.ConfidenceIntervalLower,
result.ConfidenceIntervalUpper);
streamWriter.WriteLine("Mittelwert 1. Variable: {0}", result.MeanValue1);
streamWriter.WriteLine("Mittelwert 2. Variable: {0}", result.MeanValue2);
streamWriter.WriteLine("Standardabweichung 1. Variable: {0}", result.StandardDeviation1);
streamWriter.WriteLine("Standardabweichung 2. Variable: {0}", result.StandardDeviation2);
}
}
public EffectSizeResult CalculateEffectSize()
{
var result = new EffectSizeResult();
var firstVariableValues = GetVariableValues(_cohensSettings.SelectedFirstVariable, _excelDataSet);
var secondVariableValues = GetVariableValues(_cohensSettings.SelectedSecondVariable, _excelDataSet);
var filterVariableValues = GetFilterVariableValues(_cohensSettings, _excelDataSet);
RemoveEmptyVariables(firstVariableValues, secondVariableValues, filterVariableValues);
if (filterVariableValues != null)
{
ApplyFilterToVariables(_cohensSettings.Filter, firstVariableValues, secondVariableValues, filterVariableValues);
}
result.MeanValue1 = CalculateMeanValue(firstVariableValues);
result.MeanValue2 = CalculateMeanValue(secondVariableValues);
var sigma = CalculateSigma(_cohensSettings.SameVariances, firstVariableValues, secondVariableValues, result);
result.Result = (result.MeanValue1 - result.MeanValue2) / sigma;
var correlation = CalculateCorrelation(firstVariableValues, secondVariableValues);
var standardError = CalculateStandardError(result.Result, correlation, firstVariableValues.Count);
result.ConfidenceIntervalLower = result.Result - standardError * 1.96;
result.ConfidenceIntervalUpper = result.Result + standardError * 1.96;
return result;
}
private void OnSaveResult(EffectSizeResult result)
{
_saveFileService.Filter = "Ergebnisdatei|*.txt";
if (_saveFileService.ShowDialog() == true)
{
var filename = _saveFileService.FileName;
_resultExporter.SaveResult(result, filename);
}
}
public ResultVM(EffectSizeResult result)
{
Result = result;
}
private double CalculateSigma(
bool sameVariances,
List<double> firstVariableValues,
List<double> secondVariableValues,
EffectSizeResult effectSizeResult)
{
double sigma;
if (sameVariances)
{
sigma = CalculateVariance(firstVariableValues);
sigma = Math.Sqrt(sigma);
}
else
{
var variance1 = CalculateVariance(firstVariableValues);
effectSizeResult.StandardDeviation1 = Math.Sqrt(variance1);
var variance2 = CalculateVariance(secondVariableValues);
effectSizeResult.StandardDeviation2 = Math.Sqrt(variance2);
var summand1 = (firstVariableValues.Count - 1) * variance1;
var summand2 = (secondVariableValues.Count - 1) * variance2;
var sum = summand1 + summand2;
var bla = sum / (firstVariableValues.Count + secondVariableValues.Count);
sigma = Math.Sqrt(bla);
}
return sigma;
}
public void SaveResult(EffectSizeResult result, string filename)
{
// TODO: implement saving result.
}