/*
* This file is part of ADDIS (Aggregate Data Drug Information System).
* ADDIS is distributed from http://drugis.org/.
* Copyright © 2009 Gert van Valkenhoef, Tommi Tervonen.
* Copyright © 2010 Gert van Valkenhoef, Tommi Tervonen, Tijs Zwinkels,
* Maarten Jacobs, Hanno Koeslag, Florin Schimbinschi, Ahmad Kamal, Daniel
* Reid.
* Copyright © 2011 Gert van Valkenhoef, Ahmad Kamal, Daniel Reid, Florin
* Schimbinschi.
* Copyright © 2012 Gert van Valkenhoef, Daniel Reid, Joël Kuiper, Wouter
* Reckman.
* Copyright © 2013 Gert van Valkenhoef, Joël Kuiper.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
package org.drugis.addis.mcmcmodel;
import gov.lanl.yadas.ArgumentMaker;
import gov.lanl.yadas.BasicMCMCBond;
import gov.lanl.yadas.ConstantArgument;
import gov.lanl.yadas.IdentityArgument;
import gov.lanl.yadas.MCMCParameter;
import java.util.List;
import org.drugis.addis.entities.ContinuousMeasurement;
import org.drugis.common.stat.EstimateWithPrecision;
public class BaselineMeanDifferenceModel extends AbstractBaselineModel<ContinuousMeasurement> {
public BaselineMeanDifferenceModel(List<ContinuousMeasurement> measurements) {
super(measurements);
}
@Override
protected void createDataBond(MCMCParameter studyMu) {
new BasicMCMCBond(new MCMCParameter[] {studyMu},
new ArgumentMaker[] {
new ConstantArgument(meanArray()),
new IdentityArgument(0),
new ConstantArgument(standardErrorArray())
}, new gov.lanl.yadas.Gaussian());
}
private double[] standardErrorArray() {
double[] arr = new double[d_measurements.size()];
for (int i = 0; i < arr.length; ++i) {
arr[i] = getError(i);
}
return arr;
}
@Override
public double getError(int i) {
return d_measurements.get(i).getStdDev() / Math.sqrt(d_measurements.get(i).getSampleSize());
}
private double[] meanArray() {
double[] arr = new double[d_measurements.size()];
for (int i = 0; i < arr.length; ++i) {
arr[i] = getMean(i);
}
return arr;
}
private Double getMean(int i) {
return d_measurements.get(i).getMean();
}
@Override
protected EstimateWithPrecision estimateTreatmentEffect(int i) {
return new EstimateWithPrecision(getMean(i), getError(i));
}
}