protected override void worker_DoWork(object sender, System.ComponentModel.DoWorkEventArgs e)
{
Configuration config = dashboardHelper.Config;
Dictionary<string, string> setProperties = new Dictionary<string, string>();
setProperties.Add("BLabels", config.Settings.RepresentationOfYes + ";" + config.Settings.RepresentationOfNo + ";" + config.Settings.RepresentationOfMissing); // TODO: Replace Yes, No, Missing with global vars
bool includeMissing = true;
Dictionary<string, string> inputVariableList = GadgetOptions.InputVariableList;
lock (syncLock)
{
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToProcessingState));
this.Dispatcher.BeginInvoke(new SimpleCallback(ClearResults));
SetGridTextDelegate setText = new SetGridTextDelegate(SetGridText);
AddGridRowDelegate addRow = new AddGridRowDelegate(AddGridRow);
System.Collections.Generic.Dictionary<string, System.Data.DataTable> Freq_ListSet = new Dictionary<string, System.Data.DataTable>();
string customFilter = string.Empty;
List<string> columnNames = new List<string>();
foreach (KeyValuePair<string, string> kvp in inputVariableList)
{
if (kvp.Key.ToLower().Equals("includemissing"))
{
includeMissing = bool.Parse(kvp.Value);
}
}
foreach (KeyValuePair<string, string> kvp in inputVariableList)
{
if (kvp.Value.ToLower().Equals("unsorted") || kvp.Value.ToLower().Equals("dependvar") || kvp.Value.ToLower().Equals("weightvar") || kvp.Value.ToLower().Equals("matchvar"))
{
columnNames.Add(kvp.Key);
if (!kvp.Value.ToLower().Equals("dependvar"))
{
customFilter = customFilter + StringLiterals.PARANTHESES_OPEN + StringLiterals.LEFT_SQUARE_BRACKET + kvp.Key + StringLiterals.RIGHT_SQUARE_BRACKET + StringLiterals.SPACE + "is not null" + StringLiterals.PARANTHESES_CLOSE + " AND ";
}
}
else if (kvp.Value.ToLower().Equals("discrete"))
{
columnNames.Add(kvp.Key);
customFilter = customFilter + StringLiterals.PARANTHESES_OPEN + StringLiterals.LEFT_SQUARE_BRACKET + kvp.Key + StringLiterals.RIGHT_SQUARE_BRACKET + StringLiterals.SPACE + "is not null" + StringLiterals.PARANTHESES_CLOSE + " AND ";
}
}
if (includeMissing)
{
customFilter = string.Empty;
}
else
{
customFilter = customFilter.Remove(customFilter.Length - 4, 4);
}
try
{
lock (staticSyncLock)
{
DataTable regressTable = dashboardHelper.GenerateTable(columnNames, customFilter);
RegressionResults results = new RegressionResults();
if (regressTable == null || regressTable.Rows.Count <= 0)
{
this.Dispatcher.BeginInvoke(new RenderFinishWithErrorDelegate(RenderFinishWithError), SharedStrings.NO_RECORDS_SELECTED);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
Debug.Print("Thread stopped due to errors.");
return;
}
else if (worker.CancellationPending)
{
this.Dispatcher.BeginInvoke(new RenderFinishWithErrorDelegate(RenderFinishWithError), SharedStrings.DASHBOARD_GADGET_STATUS_OPERATION_CANCELLED);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
Debug.Print("Thread cancelled");
return;
}
else
{
StatisticsRepository.LogisticRegression logisticRegression = new StatisticsRepository.LogisticRegression();
results.regressionResults = logisticRegression.LogisticRegression(inputVariableList, regressTable);
results.casesIncluded = results.regressionResults.casesIncluded;
results.convergence = results.regressionResults.convergence;
results.finalLikelihood = results.regressionResults.finalLikelihood;
results.iterations = results.regressionResults.iterations;
results.LRDF = results.regressionResults.LRDF;
results.LRP = results.regressionResults.LRP;
results.LRStatistic = results.regressionResults.LRStatistic;
results.scoreDF = results.regressionResults.scoreDF;
results.scoreP = results.regressionResults.scoreP;
results.scoreStatistic = results.regressionResults.scoreStatistic;
results.errorMessage = results.regressionResults.errorMessage.Replace("<tlt>", string.Empty).Replace("</tlt>", string.Empty);
results.variables = new List<VariableRow>();
if (!string.IsNullOrEmpty(results.errorMessage))
{
throw new ApplicationException(results.errorMessage);
}
if (results.regressionResults.variables != null)
{
foreach (StatisticsRepository.LogisticRegression.VariableRow vrow in results.regressionResults.variables)
{
VariableRow nrow = new VariableRow();
nrow.coefficient = vrow.coefficient;
nrow.ci = vrow.ci;
nrow.P = vrow.P;
nrow.ninetyFivePercent = vrow.ninetyFivePercent;
nrow.oddsRatio = vrow.oddsRatio;
nrow.se = vrow.se;
nrow.variableName = vrow.variableName;
nrow.Z = vrow.Z;
results.variables.Add(nrow);
}
this.Dispatcher.BeginInvoke(new SimpleCallback(RenderRegressionHeader));
int rowCount = 1;
foreach (VariableRow row in results.variables)
{
this.Dispatcher.Invoke(addRow, grdRegress, 30);
string displayValue = row.variableName;
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(displayValue, new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Left, TextAlignment.Left, rowCount, 0, Visibility.Visible));
if (row.oddsRatio <= -9999)
{
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig("*", new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 1, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig("*", new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 2, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig("*", new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 3, Visibility.Visible));
}
else
{
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(row.oddsRatio.ToString("F4"), new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 1, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(row.ninetyFivePercent.ToString("F4"), new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 2, Visibility.Visible));
if (row.ci > 1.0E12)
{
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(">1.0E12", new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 3, Visibility.Visible));
}
else
{
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(row.ci.ToString("F4"), new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 3, Visibility.Visible));
}
}
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(row.coefficient.ToString("F4"), new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 4, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(row.se.ToString("F4"), new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 5, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(row.Z.ToString("F4"), new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 6, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(row.P.ToString("F4"), new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 7, Visibility.Visible));
rowCount++;
}
if (results.regressionResults.interactionOddsRatios != null)
{
this.Dispatcher.BeginInvoke(new SimpleCallback(RenderIORHeader));
rowCount = 1;
foreach (StatisticsRepository.LogisticRegression.InteractionRow ir in results.regressionResults.interactionOddsRatios)
{
this.Dispatcher.Invoke(addRow, grdIOR, 30);
this.Dispatcher.BeginInvoke(setText, grdIOR, new TextBlockConfig(ir.interactionName.ToString(), new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Left, TextAlignment.Right, rowCount, 0, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdIOR, new TextBlockConfig(ir.oddsRatio.ToString(), new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Left, TextAlignment.Right, rowCount, 1, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdIOR, new TextBlockConfig(ir.ninetyFivePercent.ToString(), new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Left, TextAlignment.Right, rowCount, 2, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdIOR, new TextBlockConfig(ir.ci.ToString(), new Thickness(4, 0, 4, 0), VerticalAlignment.Center, HorizontalAlignment.Left, TextAlignment.Right, rowCount, 3, Visibility.Visible));
rowCount++;
}
}
this.Dispatcher.BeginInvoke(new SimpleCallback(DrawRegressionBorders));
}
}
this.Dispatcher.BeginInvoke(new RenderGridDelegate(RenderRegressionResults), results);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
}
}
catch (Exception ex)
{
this.Dispatcher.BeginInvoke(new RenderFinishWithErrorDelegate(RenderFinishWithError), ex.Message);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
}
finally
{
stopwatch.Stop();
Debug.Print("Logistic regression gadget took " + stopwatch.Elapsed.ToString() + " seconds to complete with " + dashboardHelper.RecordCount.ToString() + " records and the following filters:");
Debug.Print(dashboardHelper.DataFilters.GenerateDataFilterString());
//gridCells.singleTableResults = new StatisticsRepository.cTable().SigTable((double)gridCells.yyVal, (double)gridCells.ynVal, (double)gridCells.nyVal, (double)gridCells.nnVal, 0.95);
}
}
}
private void RenderRegressionResults(RegressionResults results)
{
txtConvergence.Visibility = Visibility.Visible;
txtIterations.Visibility = Visibility.Visible;
txtFinalLog.Visibility = Visibility.Visible;
txtCasesIncluded.Visibility = Visibility.Visible;
txtConvergenceLabel.Visibility = Visibility.Visible;
txtIterationsLabel.Visibility = Visibility.Visible;
txtFinalLogLabel.Visibility = Visibility.Visible;
txtCasesIncludedLabel.Visibility = Visibility.Visible;
grdRegress.Visibility = System.Windows.Visibility.Visible;
grdIOR.Visibility = System.Windows.Visibility.Visible;
grdStats.Visibility = System.Windows.Visibility.Visible;
grdParameters.Visibility = System.Windows.Visibility.Visible;
waitPanel.Visibility = System.Windows.Visibility.Collapsed;
btnRun.IsEnabled = true;
if (!string.IsNullOrEmpty(results.errorMessage) || results.variables == null)
{
grdParameters.Visibility = System.Windows.Visibility.Hidden;
grdStats.Visibility = System.Windows.Visibility.Visible;
txtConvergence.Text = string.Empty;
txtIterations.Text = string.Empty;
txtFinalLog.Text = string.Empty;
txtCasesIncluded.Text = string.Empty;
txtIterationsLabel.Text = string.Empty;
txtFinalLogLabel.Text = string.Empty;
txtCasesIncludedLabel.Text = string.Empty;
txtConvergenceLabel.Text = results.errorMessage;
txtConvergenceLabel.TextWrapping = TextWrapping.Wrap;
}
else
{
grdParameters.Visibility = System.Windows.Visibility.Visible;
grdStats.Visibility = System.Windows.Visibility.Visible;
txtScoreStatistic.Text = StringLiterals.SPACE + results.scoreStatistic.ToString("F4") + StringLiterals.SPACE;
txtScoreDF.Text = StringLiterals.SPACE + results.scoreDF.ToString() + StringLiterals.SPACE;
txtScoreP.Text = StringLiterals.SPACE + results.scoreP.ToString("F4") + StringLiterals.SPACE;
txtLStatistic.Text = StringLiterals.SPACE + results.LRStatistic.ToString("F4") + StringLiterals.SPACE;
txtLDF.Text = StringLiterals.SPACE + results.LRDF.ToString() + StringLiterals.SPACE;
txtLP.Text = StringLiterals.SPACE + results.LRP.ToString("F4") + StringLiterals.SPACE;
txtConvergence.Text = results.convergence;
txtIterations.Text = StringLiterals.SPACE + results.iterations.ToString() + StringLiterals.SPACE;
txtFinalLog.Text = StringLiterals.SPACE + results.finalLikelihood.ToString("F4") + StringLiterals.SPACE;
txtCasesIncluded.Text = StringLiterals.SPACE + results.casesIncluded.ToString() + StringLiterals.SPACE;
txtConvergenceLabel.Text = "Convergence:";
txtIterationsLabel.Text ="Iterations:";
txtFinalLogLabel.Text = "Final -2*Log-Likelihood:";
txtCasesIncludedLabel.Text = "Cases Included:";
}
}
protected override void worker_DoWork(object sender, System.ComponentModel.DoWorkEventArgs e)
{
lock (syncLock)
{
Configuration config = DashboardHelper.Config;
Dictionary<string, string> setProperties = new Dictionary<string, string>();
setProperties.Add("Intercept", "true");
setProperties.Add("P", 0.95.ToString());
setProperties.Add("BLabels", config.Settings.RepresentationOfYes + ";" + config.Settings.RepresentationOfNo + ";" + config.Settings.RepresentationOfMissing); // TODO: Replace Yes, No, Missing with global vars
//Dictionary<string, string> inputVariableList = (Dictionary<string, string>)e.Argument;
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToProcessingState));
this.Dispatcher.BeginInvoke(new SimpleCallback(ClearResults));
SetGridTextDelegate setText = new SetGridTextDelegate(SetGridText);
AddGridRowDelegate addRow = new AddGridRowDelegate(AddGridRow);
//SetGridBarDelegate setBar = new SetGridBarDelegate(SetGridBar);
System.Collections.Generic.Dictionary<string, System.Data.DataTable> Freq_ListSet = new Dictionary<string, System.Data.DataTable>();
//string customFilter = string.Empty;
List<string> columnNames = new List<string>();
foreach (KeyValuePair<string, string> kvp in GadgetOptions.InputVariableList)
{
if (kvp.Value.ToLower().Equals("unsorted") || kvp.Value.ToLower().Equals("dependvar") || kvp.Value.ToLower().Equals("weightvar") || kvp.Value.ToLower().Equals("matchvar"))
{
columnNames.Add(kvp.Key);
}
else if (kvp.Value.ToLower().Equals("discrete"))
{
columnNames.Add(kvp.Key);
}
}
try
{
lock (staticSyncLock)
{
RequestUpdateStatusDelegate requestUpdateStatus = new RequestUpdateStatusDelegate(RequestUpdateStatusMessage);
CheckForCancellationDelegate checkForCancellation = new CheckForCancellationDelegate(IsCancelled);
GadgetOptions.GadgetStatusUpdate += new GadgetStatusUpdateHandler(requestUpdateStatus);
GadgetOptions.GadgetCheckForCancellation += new GadgetCheckForCancellationHandler(checkForCancellation);
DataTable regressTable = DashboardHelper.GenerateTable(columnNames);
RegressionResults results = new RegressionResults();
if (regressTable == null || regressTable.Rows.Count <= 0)
{
this.Dispatcher.BeginInvoke(new RenderFinishWithErrorDelegate(RenderFinishWithError), SharedStrings.NO_RECORDS_SELECTED);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
Debug.Print("Thread stopped due to errors.");
return;
}
else if (worker.CancellationPending)
{
this.Dispatcher.BeginInvoke(new RenderFinishWithErrorDelegate(RenderFinishWithError), SharedStrings.DASHBOARD_GADGET_STATUS_OPERATION_CANCELLED);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
Debug.Print("Thread cancelled");
return;
}
else
{
StatisticsRepository.LinearRegression linearRegression = new StatisticsRepository.LinearRegression();
results.regressionResults = linearRegression.LinearRegression(GadgetOptions.InputVariableList, regressTable);
results.correlationCoefficient = results.regressionResults.correlationCoefficient;
results.regressionDf = results.regressionResults.regressionDf;
results.regressionF = results.regressionResults.regressionF;
results.regressionMeanSquare = results.regressionResults.regressionMeanSquare;
results.regressionSumOfSquares = results.regressionResults.regressionSumOfSquares;
results.residualsDf = results.regressionResults.residualsDf;
results.residualsMeanSquare = results.regressionResults.residualsMeanSquare;
results.residualsSumOfSquares = results.regressionResults.residualsSumOfSquares;
results.totalDf = results.regressionResults.totalDf;
results.totalSumOfSquares = results.regressionResults.totalSumOfSquares;
results.errorMessage = results.regressionResults.errorMessage.Replace("<tlt>", string.Empty).Replace("</tlt>", string.Empty);
if (!string.IsNullOrEmpty(results.errorMessage))
{
throw new ApplicationException(results.errorMessage);
}
results.variables = new List<VariableRow>();
if (results.regressionResults.variables != null)
{
double tScore = 1.9;
while (Epi.Statistics.SharedResources.PFromT(tScore, results.residualsDf) > 0.025)
{
tScore += 0.000001;
}
foreach (StatisticsRepository.LinearRegression.VariableRow vrow in results.regressionResults.variables)
{
VariableRow nrow = new VariableRow();
nrow.coefficient = vrow.coefficient;
nrow.Ftest = vrow.Ftest;
nrow.P = vrow.P;
nrow.stdError = vrow.stdError;
nrow.variableName = vrow.variableName;
nrow.coefficientLower = nrow.coefficient - tScore * nrow.stdError;
nrow.coefficientUpper = nrow.coefficient + tScore * nrow.stdError;
results.variables.Add(nrow);
}
results.regressionFp = Epi.Statistics.SharedResources.PFromF(results.regressionF, results.regressionDf, results.residualsDf);
this.Dispatcher.BeginInvoke(new SimpleCallback(RenderRegressionHeader));
int rowCount = 1;
foreach (VariableRow row in results.variables)
{
this.Dispatcher.Invoke(addRow, grdRegress, 30);
string displayValue = row.variableName;
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + displayValue + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Left, TextAlignment.Left, rowCount, 0, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + row.coefficient.ToString("F3") + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 1, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + row.coefficientLower.ToString("F3") + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 2, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + row.coefficientUpper.ToString("F3") + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 3, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + row.stdError.ToString("F3") + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 4, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + row.Ftest.ToString("F4") + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 5, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + row.P.ToString("F6") + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 6, Visibility.Visible));
rowCount++;
}
//this.Dispatcher.BeginInvoke(new AddGridFooterDelegate(RenderFrequencyFooter), rowCount, count);
this.Dispatcher.BeginInvoke(new SimpleCallback(DrawRegressionBorders));
}
}
this.Dispatcher.BeginInvoke(new RenderGridDelegate(RenderRegressionResults), results);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
}
}
catch (Exception ex)
{
this.Dispatcher.BeginInvoke(new RenderFinishWithErrorDelegate(RenderFinishWithError), ex.Message);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
}
finally
{
stopwatch.Stop();
Debug.Print("Linear regression gadget took " + stopwatch.Elapsed.ToString() + " seconds to complete with " + DashboardHelper.RecordCount.ToString() + " records and the following filters:");
Debug.Print(DashboardHelper.DataFilters.GenerateDataFilterString());
}
}
//gridCells.singleTableResults = new StatisticsRepository.cTable().SigTable((double)gridCells.yyVal, (double)gridCells.ynVal, (double)gridCells.nyVal, (double)gridCells.nnVal, 0.95);
}
public void MatchedLogisticRegressionTest()
{
int iterations = 100;
var reader = new StreamReader(File.OpenRead(@"..\..\Data\MatchedLogisticCoefficientResults.csv"));
int linesinfile = 2 * iterations;
double[] coefficients = new double[linesinfile];
double[] stderrs = new double[linesinfile];
double[] chisqs = new double[linesinfile];
double[] ps = new double[linesinfile];
int i = 0;
while (!reader.EndOfStream)
{
var line = reader.ReadLine();
var values = line.Split(',');
bool rv = Double.TryParse(values[2], out coefficients[i]);
rv = Double.TryParse(values[3], out stderrs[i]);
rv = Double.TryParse(values[4], out chisqs[i]);
rv = Double.TryParse(values[5], out ps[i]);
i++;
if (i == linesinfile)
{
break;
}
}
reader = new StreamReader(File.OpenRead(@"..\..\Data\MatchedLogisticOddsRatioResults.csv"));
linesinfile = 2 * iterations;
double[] oddsratios = new double[linesinfile];
double[] lowercls = new double[linesinfile];
double[] uppercls = new double[linesinfile];
i = 0;
while (!reader.EndOfStream)
{
var line = reader.ReadLine();
var values = line.Split(',');
bool rv = Double.TryParse(values[2], out oddsratios[i]);
rv = Double.TryParse(values[3], out lowercls[i]);
rv = Double.TryParse(values[4], out uppercls[i]);
i++;
if (i == linesinfile)
{
break;
}
}
reader = new StreamReader(File.OpenRead(@"..\..\Data\MatchedLogisticGlobalTestResults.csv"));
linesinfile = 2 * iterations;
double[] globalchisqs = new double[linesinfile];
double[] dfs = new double[linesinfile];
double[] probchisqs = new double[linesinfile];
i = 0;
while (!reader.EndOfStream)
{
var line = reader.ReadLine();
var values = line.Split(',');
bool rv = Double.TryParse(values[2], out globalchisqs[i]);
rv = Double.TryParse(values[3], out dfs[i]);
rv = Double.TryParse(values[4], out probchisqs[i]);
i++;
if (i == linesinfile)
{
break;
}
}
reader = new StreamReader(File.OpenRead(@"..\..\Data\MatchedLogisticFitStatisticResults.csv"));
linesinfile = iterations;
double[] withcovariates = new double[linesinfile];
i = 0;
while (!reader.EndOfStream)
{
var line = reader.ReadLine();
var values = line.Split(',');
bool rv = Double.TryParse(values[1], out withcovariates[i]);
i++;
if (i == linesinfile)
{
break;
}
}
for (int j = 0; j < iterations; j++)
{
getData("MatchedLogisticTestData", "iteration = " + j);
Dictionary <string, string> inputVariableList = new Dictionary <string, string>();
inputVariableList.Add("case", "dependvar");
inputVariableList.Add("intercept", "true");
inputVariableList.Add("includemissing", "false");
inputVariableList.Add("GROUPID", "matchvar");
inputVariableList.Add("P", "0.95");
inputVariableList.Add("indepvar1", "unsorted");
inputVariableList.Add("indepvar2", "unsorted");
DataTable regressTable = new DataTable();
RegressionResults results = new RegressionResults();
StatisticsRepository.LogisticRegression logisticRegression = new StatisticsRepository.LogisticRegression();
results.regressionResults = logisticRegression.LogisticRegression(inputVariableList, mainTable);
if (false)
{
System.Diagnostics.Trace.Write(results.regressionResults.variables[0].oddsRatio + "\t" +
results.regressionResults.variables[0].ninetyFivePercent + "\t" +
results.regressionResults.variables[0].ci + "\t" +
results.regressionResults.variables[0].coefficient + "\t" +
results.regressionResults.variables[0].se + "\t" +
results.regressionResults.variables[0].Z + "\t" +
results.regressionResults.variables[0].P + "\n");
System.Diagnostics.Trace.Write(results.regressionResults.variables[1].oddsRatio + "\t" +
results.regressionResults.variables[1].ninetyFivePercent + "\t" +
results.regressionResults.variables[1].ci + "\t" +
results.regressionResults.variables[1].coefficient + "\t" +
results.regressionResults.variables[1].se + "\t" +
results.regressionResults.variables[1].Z + "\t" +
results.regressionResults.variables[1].P + "\n");
}
Assert.AreEqual(results.regressionResults.variables[0].oddsRatio, oddsratios[j * 2], 0.01);
Assert.AreEqual(results.regressionResults.variables[0].ninetyFivePercent, lowercls[j * 2], 0.01);
Assert.AreEqual(results.regressionResults.variables[0].ci, uppercls[j * 2], 0.01);
Assert.AreEqual(results.regressionResults.variables[0].coefficient, coefficients[j * 2], 0.01);
Assert.AreEqual(results.regressionResults.variables[0].se, stderrs[j * 2], 0.01);
// Assert.AreEqual(results.regressionResults.variables[0].Z, chisqs[j * 3 + 1], 0.01);
Assert.AreEqual(results.regressionResults.variables[0].P, ps[j * 2], 0.01);
Assert.AreEqual(results.regressionResults.variables[1].oddsRatio, oddsratios[j * 2 + 1], 0.01);
Assert.AreEqual(results.regressionResults.variables[1].ninetyFivePercent, lowercls[j * 2 + 1], 0.01);
Assert.AreEqual(results.regressionResults.variables[1].ci, uppercls[j * 2 + 1], 0.01);
Assert.AreEqual(results.regressionResults.variables[1].coefficient, coefficients[j * 2 + 1], 0.01);
Assert.AreEqual(results.regressionResults.variables[1].se, stderrs[j * 2 + 1], 0.01);
// Assert.AreEqual(results.regressionResults.variables[1].Z, chisqs[j * 3 + 2], 0.01);
Assert.AreEqual(results.regressionResults.variables[1].P, ps[j * 2 + 1], 0.01);
Assert.AreEqual(results.regressionResults.finalLikelihood, withcovariates[j], 0.0001);
Assert.AreEqual(results.regressionResults.LRStatistic, globalchisqs[j * 2], 0.0001);
Assert.AreEqual(results.regressionResults.scoreStatistic, globalchisqs[j * 2 + 1], 0.0001);
Assert.AreEqual(results.regressionResults.LRDF, dfs[j * 2], 0.0001);
Assert.AreEqual(results.regressionResults.scoreDF, dfs[j * 2 + 1], 0.0001);
Assert.AreEqual(results.regressionResults.LRP, probchisqs[j * 2], 0.0001);
Assert.AreEqual(results.regressionResults.scoreP, probchisqs[j * 2 + 1], 0.0001);
}
}
private void RenderRegressionResults(RegressionResults results)
{
txtCorrelation.Visibility = Visibility.Visible;
//waitCursor.Visibility = Visibility.Collapsed;
waitPanel.Visibility = System.Windows.Visibility.Collapsed;
grdParameters.Visibility = Visibility.Visible;
grdRegress.Visibility = System.Windows.Visibility.Visible;
btnRun.IsEnabled = true;
if (!string.IsNullOrEmpty(results.errorMessage))
{
txtCorrelation.Text = results.errorMessage;
Thickness margin = txtCorrelation.Margin;
margin.Top = 52;
txtCorrelation.Margin = margin;
grdParameters.Visibility = System.Windows.Visibility.Hidden;
}
else if (results.variables == null)
{
txtCorrelation.Text = string.Empty;
Thickness margin = txtCorrelation.Margin;
margin.Top = 8;
txtCorrelation.Margin = margin;
grdParameters.Visibility = System.Windows.Visibility.Hidden;
}
else
{
Thickness margin = txtCorrelation.Margin;
margin.Top = 8;
txtCorrelation.Margin = margin;
grdParameters.Visibility = System.Windows.Visibility.Visible;
txtRegressionDf.Text = StringLiterals.SPACE + results.regressionDf.ToString() + StringLiterals.SPACE;
txtRegressionSumOfSquares.Text = StringLiterals.SPACE + results.regressionSumOfSquares.ToString("F4") + StringLiterals.SPACE;
txtRegressionMeanSquare.Text = StringLiterals.SPACE + results.regressionMeanSquare.ToString("F4") + StringLiterals.SPACE;
txtRegressionFstatistic.Text = StringLiterals.SPACE + results.regressionF.ToString("F4") + StringLiterals.SPACE;
txtRegressionFstatisticP.Text = StringLiterals.SPACE + results.regressionFp.ToString("F4") + StringLiterals.SPACE;
txtResidualsDf.Text = StringLiterals.SPACE + results.residualsDf.ToString() + StringLiterals.SPACE;
txtResidualsSumOfSquares.Text = StringLiterals.SPACE + results.residualsSumOfSquares.ToString("F4") + StringLiterals.SPACE;
txtResidualsMeanSquare.Text = StringLiterals.SPACE + results.residualsMeanSquare.ToString("F4") + StringLiterals.SPACE;
txtTotalDf.Text = StringLiterals.SPACE + results.totalDf.ToString() + StringLiterals.SPACE;
txtTotalSumOfSquares.Text = StringLiterals.SPACE + results.totalSumOfSquares.ToString("F4") + StringLiterals.SPACE;
txtCorrelation.Text = "Correlation Coefficient: r^2 = " + results.correlationCoefficient.ToString("F2");
if (results.regressionResults.pearsonCoefficient <= 1.0)
{
grdPearson.Visibility = System.Windows.Visibility.Visible;
txtPearsonAnalysis.Visibility = System.Windows.Visibility.Visible;
txtPearsonCoefficient.Text = results.regressionResults.pearsonCoefficient.ToString("F4");
txtPearsonCoefficientT.Text = results.regressionResults.pearsonCoefficientT.ToString("F4");
txtPearsonCoefficientTP.Text = results.regressionResults.pearsonCoefficientTP.ToString("F4");
if (results.regressionResults.pearsonCoefficientTP < 0.0001)
txtPearsonCoefficientTP.Text = "<0.0001";
if (results.regressionResults.spearmanCoefficient <= 1.0)
{
grdSpearman.Visibility = System.Windows.Visibility.Visible;
txtSpearmanAnalysis.Visibility = System.Windows.Visibility.Visible;
txtSpearmanCoefficient.Text = results.regressionResults.spearmanCoefficient.ToString("F4");
txtSpearmanCoefficientT.Text = results.regressionResults.spearmanCoefficientT.ToString("F4");
txtSpearmannCoefficientTP.Text = results.regressionResults.spearmanCoefficientTP.ToString("F4");
if (results.regressionResults.spearmanCoefficientTP < 0.0001)
txtSpearmannCoefficientTP.Text = "<0.0001";
}
else
{
grdSpearman.Visibility = System.Windows.Visibility.Collapsed;
txtSpearmanAnalysis.Visibility = System.Windows.Visibility.Collapsed;
}
}
else
{
grdPearson.Visibility = System.Windows.Visibility.Collapsed;
txtPearsonAnalysis.Visibility = System.Windows.Visibility.Collapsed;
grdSpearman.Visibility = System.Windows.Visibility.Collapsed;
txtSpearmanAnalysis.Visibility = System.Windows.Visibility.Collapsed;
}
}
HideConfigPanel();
}
