Java tutorial
/* * 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, Jol Kuiper, Wouter * Reckman. * Copyright 2013 Gert van Valkenhoef, Jol 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.entities.analysis; import java.io.IOException; import java.io.ObjectInputStream; import java.util.ArrayList; import java.util.Arrays; import java.util.HashMap; import java.util.List; import java.util.Map; import org.apache.commons.collections15.CollectionUtils; import org.apache.commons.collections15.Predicate; import org.drugis.addis.entities.Arm; import org.drugis.addis.entities.Entity; import org.drugis.addis.entities.Indication; import org.drugis.addis.entities.Measurement; import org.drugis.addis.entities.OutcomeMeasure; import org.drugis.addis.entities.RateVariableType; import org.drugis.addis.entities.Study; import org.drugis.addis.entities.StudyArmsEntry; import org.drugis.addis.entities.relativeeffect.BasicMeanDifference; import org.drugis.addis.entities.relativeeffect.BasicOddsRatio; import org.drugis.addis.entities.relativeeffect.BasicRelativeEffect; import org.drugis.addis.entities.relativeeffect.GaussianBase; import org.drugis.addis.entities.relativeeffect.RandomEffectMetaAnalysisRelativeEffect; import org.drugis.addis.entities.relativeeffect.RandomEffectsRelativeEffect; import org.drugis.addis.entities.relativeeffect.RelativeEffect; import org.drugis.addis.entities.relativeeffect.RelativeEffectFactory; import org.drugis.addis.entities.treatment.TreatmentDefinition; import org.drugis.addis.util.EntityUtil; import org.drugis.mtc.summary.MultivariateNormalSummary; import org.drugis.mtc.summary.SimpleMultivariateNormalSummary; public class RandomEffectsMetaAnalysis extends AbstractMetaAnalysis implements PairWiseMetaAnalysis { private static final String ANALYSIS_TYPE = "DerSimonian-Laird Random Effects Meta-Analysis"; public static final String PROPERTY_INCLUDED_STUDIES_COUNT = "studiesIncluded"; public static final String PROPERTY_CORRECTED = "isCorrected"; private boolean d_isCorrected = false; public RandomEffectsMetaAnalysis(String name, OutcomeMeasure om, TreatmentDefinition baseline, TreatmentDefinition subject, List<StudyArmsEntry> studyArms, boolean corr) { super(ANALYSIS_TYPE, name, getIndication(studyArms), om, getStudies(studyArms), Arrays.asList(baseline, subject), getArmMap(baseline, subject, studyArms)); d_isCorrected = corr; } private static Map<Study, Map<TreatmentDefinition, Arm>> getArmMap(TreatmentDefinition baseline, TreatmentDefinition subject, List<StudyArmsEntry> studyArms) { Map<Study, Map<TreatmentDefinition, Arm>> armMap = new HashMap<Study, Map<TreatmentDefinition, Arm>>(); for (StudyArmsEntry sae : studyArms) { Map<TreatmentDefinition, Arm> alternativeMap = new HashMap<TreatmentDefinition, Arm>(); alternativeMap.put(baseline, sae.getBase()); alternativeMap.put(subject, sae.getSubject()); armMap.put(sae.getStudy(), alternativeMap); } return armMap; } private static List<Study> getStudies(List<StudyArmsEntry> studyArms) { return StudyArmsEntry.getStudyList(studyArms); } private static Indication getIndication(List<StudyArmsEntry> studyArms) { return getStudies(studyArms).get(0).getIndication(); } private void readObject(ObjectInputStream in) throws IOException, ClassNotFoundException { in.defaultReadObject(); } @Override public TreatmentDefinition getFirstAlternative() { return d_alternatives.get(0); } @Override public TreatmentDefinition getSecondAlternative() { return d_alternatives.get(1); } public List<StudyArmsEntry> getStudyArms() { List<StudyArmsEntry> studyArms = new ArrayList<StudyArmsEntry>(); for (Study s : getIncludedStudies()) { studyArms.add( new StudyArmsEntry(s, getArm(s, getFirstAlternative()), getArm(s, getSecondAlternative()))); } return studyArms; } List<RelativeEffect<? extends Measurement>> getRelativeEffects(Class<? extends RelativeEffect<?>> type) { List<RelativeEffect<? extends Measurement>> relEffects = new ArrayList<RelativeEffect<? extends Measurement>>(); for (StudyArmsEntry entry : getStudyArms()) { relEffects.add((BasicRelativeEffect<? extends Measurement>) RelativeEffectFactory .buildRelativeEffect(entry, d_outcome, type, d_isCorrected)); } return relEffects; } List<RelativeEffect<? extends Measurement>> getFilteredRelativeEffects( Class<? extends RelativeEffect<?>> type) { final List<RelativeEffect<? extends Measurement>> relativeEffects = getRelativeEffects(type); CollectionUtils.filter(relativeEffects, new Predicate<RelativeEffect<? extends Measurement>>() { public boolean evaluate(RelativeEffect<? extends Measurement> re) { return re.isDefined(); } }); return relativeEffects; } public RandomEffectMetaAnalysisRelativeEffect<Measurement> getRelativeEffect( Class<? extends RelativeEffect<?>> type) { final List<RelativeEffect<? extends Measurement>> relativeEffects = getFilteredRelativeEffects(type); if (relativeEffects.isEmpty()) { return null; } return new RandomEffectsRelativeEffect(relativeEffects); } public boolean getIsCorrected() { return d_isCorrected; } public void setIsCorrected(boolean iscorrected) { boolean oldVal = d_isCorrected; d_isCorrected = iscorrected; firePropertyChange(PROPERTY_CORRECTED, oldVal, d_isCorrected); } @Override public boolean deepEquals(Entity other) { if (!super.deepEquals(other)) { return false; } RandomEffectsMetaAnalysis o = (RandomEffectsMetaAnalysis) other; for (StudyArmsEntry s : o.getStudyArms()) { if (!EntityUtil.deepEqual(s.getBase(), getArm(s.getStudy(), o.getFirstAlternative())) || !EntityUtil.deepEqual(s.getSubject(), getArm(s.getStudy(), o.getSecondAlternative()))) { return false; } } return true; } @Override public MultivariateNormalSummary getRelativeEffectsSummary() { Class<? extends RelativeEffect<?>> type = (d_outcome.getVariableType() instanceof RateVariableType) ? BasicOddsRatio.class : BasicMeanDifference.class; RelativeEffect<Measurement> effect = getRelativeEffect(type); GaussianBase distribution = (GaussianBase) effect.getDistribution(); return new SimpleMultivariateNormalSummary(new double[] { distribution.getMu() }, new double[][] { { distribution.getSigma() * distribution.getSigma() } }); } }