/*
* 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.entities.relativeeffect;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertFalse;
import org.drugis.addis.entities.BasicRateMeasurement;
import org.drugis.addis.entities.RateMeasurement;
import org.drugis.addis.entities.treatment.TreatmentDefinition;
import org.drugis.common.Interval;
import org.junit.Before;
import org.junit.Test;
public class BasicOddsRatioTest extends RelativeEffectTestBase {
private BasicOddsRatio d_ratioBennie, d_ratioBoyer, d_ratioFava, d_ratioNewhouse, d_ratioSechter;
@Before
public void setUp() {
d_ratioBennie = (BasicOddsRatio) RelativeEffectFactory.buildRelativeEffect(d_bennie, d_rateEndpoint, TreatmentDefinition.createTrivial(d_fluox), TreatmentDefinition.createTrivial(d_sertr), BasicOddsRatio.class);
d_ratioBoyer = (BasicOddsRatio) RelativeEffectFactory.buildRelativeEffect(d_boyer, d_rateEndpoint, TreatmentDefinition.createTrivial(d_fluox), TreatmentDefinition.createTrivial(d_sertr), BasicOddsRatio.class);
d_ratioFava = (BasicOddsRatio) RelativeEffectFactory.buildRelativeEffect(d_fava, d_rateEndpoint, TreatmentDefinition.createTrivial(d_fluox), TreatmentDefinition.createTrivial(d_sertr), BasicOddsRatio.class);
d_ratioNewhouse = (BasicOddsRatio) RelativeEffectFactory.buildRelativeEffect(d_newhouse, d_rateEndpoint, TreatmentDefinition.createTrivial(d_fluox), TreatmentDefinition.createTrivial(d_sertr), BasicOddsRatio.class);
d_ratioSechter = (BasicOddsRatio) RelativeEffectFactory.buildRelativeEffect(d_sechter, d_rateEndpoint, TreatmentDefinition.createTrivial(d_fluox), TreatmentDefinition.createTrivial(d_sertr), BasicOddsRatio.class);
}
@Test
public void testGetMean() {
assertEquals(1.36, (d_ratioBennie.getConfidenceInterval().getPointEstimate()), 0.01);
assertEquals(1.03, (d_ratioBoyer.getConfidenceInterval().getPointEstimate()), 0.01);
assertEquals(1.65, (d_ratioFava.getConfidenceInterval().getPointEstimate()), 0.01);
assertEquals(1.11, (d_ratioNewhouse.getConfidenceInterval().getPointEstimate()), 0.01);
assertEquals(1.56, (d_ratioSechter.getConfidenceInterval().getPointEstimate()), 0.01);
}
@Test
public void testGetError() {
double expected = Math.sqrt(1/63D + 1/73D + 1/(144D-63D) + 1/(142D-73D));
assertEquals(expected, d_ratioBennie.getError(), 0.001);
}
@Test
public void testGetConfidenceIntervalBennie() {
Interval<Double> ival = d_ratioBennie.getConfidenceInterval();
assertEquals(0.85, (ival.getLowerBound()), 0.01);
assertEquals(2.17, (ival.getUpperBound()), 0.01);
}
@Test
public void testGetConfidenceIntervalBoyer() {
Interval<Double> ival = d_ratioBoyer.getConfidenceInterval();
assertEquals(0.62, (ival.getLowerBound()), 0.01);
assertEquals(1.71, (ival.getUpperBound()), 0.01);
}
@Test
public void testGetConfidenceIntervalFava() {
Interval<Double> ival = d_ratioFava.getConfidenceInterval();
assertEquals(0.89, (ival.getLowerBound()), 0.01);
assertEquals(3.06, (ival.getUpperBound()), 0.015);
}
@Test
public void testGetConfidenceIntervalNewhouse() {
Interval<Double> ival = d_ratioNewhouse.getConfidenceInterval();
assertEquals(0.63, (ival.getLowerBound()), 0.01);
assertEquals(1.95, (ival.getUpperBound()), 0.01);
}
@Test
public void testGetConfidenceIntervalSechter() {
Interval<Double> ival = d_ratioSechter.getConfidenceInterval();
assertEquals(0.90, (ival.getLowerBound()), 0.01);
assertEquals(2.70, (ival.getUpperBound()), 0.01);
}
@Test public void testGetDistribution() {
Distribution distribution = d_ratioSechter.getDistribution();
assertEquals(0.90, distribution.getQuantile(0.025), 0.01);
assertEquals(2.70, distribution.getQuantile(0.975), 0.01);
}
@Test
public void testZeroBaselineRateShouldBeUndefined() {
RateMeasurement base = new BasicRateMeasurement(0, 100);
RateMeasurement subj = new BasicRateMeasurement(50, 100);
BasicOddsRatio or = new BasicOddsRatio(base, subj);
assertFalse(or.isDefined());
}
@Test
public void testFullSubjectRateShouldBeUndefined() {
RateMeasurement base = new BasicRateMeasurement(50, 100);
RateMeasurement subj = new BasicRateMeasurement(100, 100);
BasicOddsRatio or = new BasicOddsRatio(base, subj);
assertFalse(or.isDefined());
}
@Test
public void testZeroSubjectRateShouldBeUndefined() { // although we can calculate a point-estimate, we can't get a CI.
RateMeasurement base = new BasicRateMeasurement(50, 100);
RateMeasurement subj = new BasicRateMeasurement(0, 100);
BasicOddsRatio or = new BasicOddsRatio(base, subj);
assertFalse(or.isDefined());
}
@Test
public void testFullBaselineRateShouldBeUndefined() { // although we can calculate a point-estimate, we can't get a CI.
RateMeasurement base = new BasicRateMeasurement(100, 100);
RateMeasurement subj = new BasicRateMeasurement(50, 100);
BasicOddsRatio or = new BasicOddsRatio(base, subj);
assertFalse(or.isDefined());
}
@Test
public void testUndefinedShouldResultInNaN() {
RateMeasurement rmA1 = new BasicRateMeasurement(0, 100);
RateMeasurement rmC1 = new BasicRateMeasurement(50, 100);
BasicOddsRatio or = new BasicOddsRatio(rmA1, rmC1);
assertEquals(Double.NaN, or.getError(), 0.001);
assertEquals(Double.NaN, or.getConfidenceInterval().getPointEstimate(), 0.001);
}
}