/* * 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)); } }