ComputePower() 공개 메소드

Computes the power for a test with givens values of effect size and number of samples under IPowerAnalysis.Size.
public ComputePower ( ) : void
리턴 void
        public void TTestPowerAnalysisConstructorTest3()
        {
            // Examples from R's graphical manual
            // http://rgm2.lab.nig.ac.jp/RGM2/func.php?rd_id=pwr:pwr.t.test

            double actual, expected;

            {
                var target = new TTestPowerAnalysis(OneSampleHypothesis.ValueIsDifferentFromHypothesis)
                {
                    Effect = 0.2,
                    Samples = 60,
                    Size = 0.10,
                };

                target.ComputePower();

                expected = 0.4555818;
                actual = target.Power;
                Assert.AreEqual(expected, actual, 1e-5);
            }

            {
                var target = new TwoSampleTTestPowerAnalysis(TwoSampleHypothesis.ValuesAreDifferent)
                {
                    Effect = 2 / 2.8,
                    Samples1 = 30,
                    Samples2 = 30,
                };

                target.ComputePower();

                expected = 0.7764889;
                actual = target.Power;
                Assert.AreEqual(expected, actual, 1e-6);
            }

            {
                var target = new TwoSampleTTestPowerAnalysis(TwoSampleHypothesis.FirstValueIsGreaterThanSecond)
                {
                    Effect = 0.3,
                    Power = 0.75,
                };

                target.ComputeSamples();

                expected = 120.2232016;
                actual = target.Samples1;
                Assert.AreEqual(expected, actual, 1e-6);
                Assert.AreEqual(target.Samples1, target.Samples2);
            }
        }
        public void TTestPowerAnalysisConstructorTest7()
        {
            // When creating a power analysis, we have three things we can
            // change. We can always freely configure two of those things
            // and then ask the analysis to give us the third.

            var analysis = new TTestPowerAnalysis(OneSampleHypothesis.ValueIsDifferentFromHypothesis);

            // Those are:
            double e = analysis.Effect;   // the test's minimum detectable effect size
            double n = analysis.Samples;  // the number of samples in the test
            double p = analysis.Power;    // the probability of committing a type-2 error

            // Let's set the desired effect size and the 
            // number of samples so we can get the power

            analysis.Effect = 0.2; // we would like to detect at least 0.2 std. dev. apart
            analysis.Samples = 60; // we would like to use at most 60 samples
            analysis.ComputePower(); // what will be the power of this test?

            double power = analysis.Power; // The power is going to be 0.33 (or 33%)

            // Let's set the desired power and the number 
            // of samples so we can get the effect size

            analysis.Power = 0.8;  // we would like to create a test with 80% power
            analysis.Samples = 60; // we would like to use at most 60 samples
            analysis.ComputeEffect(); // what would be the minimum effect size we can detect?

            double effect = analysis.Effect; // The effect will be 0.36 standard deviations.

            // Let's set the desired power and the effect
            // size so we can get the number of samples

            analysis.Power = 0.8;  // we would like to create a test with 80% power
            analysis.Effect = 0.2; // we would like to detect at least 0.2 std. dev. apart
            analysis.ComputeSamples(); 

            double samples = analysis.Samples; // We would need around 199 samples.

            Assert.AreEqual(198.15082094251142, samples, 1e-10);
            Assert.AreEqual(0.36770431608203374, effect);
            Assert.AreEqual(0.33167864622935495, power);
        }