public void KaplanMeierTest1()
{
// Example from
// http://sas-and-r.blogspot.fr/2010/05/example-738-kaplan-meier-survival.html
double[] times;
SurvivalOutcome[] censor;
CreateExample1(out times, out censor);
var distribution = new EmpiricalHazardDistribution(SurvivalEstimator.KaplanMeier);
Assert.AreEqual(SurvivalEstimator.KaplanMeier, distribution.Estimator);
distribution.Fit(times, new EmpiricalHazardOptions(HazardEstimator.KaplanMeier, censor));
int[] t = { 1, 2, 3, 4, 6, 8, 9, 12, 14, 20 };
double[] e = { 0.889, 0.833, 0.774, 0.714, 0.649, 0.577, 0.505, 0.421, 0.337, 0.168 };
double[] actual = t.ToDouble().Apply(distribution.ComplementaryDistributionFunction);
for (int i = 0; i < e.Length; i++)
{
Assert.AreEqual(e[i], actual[i], 1e-3);
}
// Assert.AreEqual(11.177, distribution.Mean);
Assert.AreEqual(12, distribution.Median, 1e-5);
}
public void LeukemiaExampleCensoring_KaplanMeier_FlemingHarrington()
{
// The following are times of remission (weeks) for 21 leukemia
// patients receiving control treatment (Table 1.1 of Cox & Oakes):
double[] t = { 6, 6, 6, 6, 7, 9, 10, 10, 11, 13, 16, 17, 19, 20, 22, 23, 25, 32, 32, 34, 35 };
int[] c = { 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0 };
var distribution = new EmpiricalHazardDistribution(SurvivalEstimator.FlemingHarrington);
distribution.Fit(t, new SurvivalOptions {
Outcome = c.To <SurvivalOutcome[]>()
});
int[] intervals = { 6, 7, 9, 10, 11, 13, 16, 17, 19, 20, 22, 23, 25, 32, 34, 35 };
double[] expected =
{
0.8571, 0.8067, 0.8067, 0.7529, 0.7529, 0.6902,
0.6275, 0.6275, 0.6275, 0.6275, 0.5378, 0.4482,
0.4482, 0.4482, 0.4482, 0.4482
};
for (int i = 0; i < intervals.Length; i++)
{
double x = intervals[i];
double actual = distribution.ComplementaryDistributionFunction(x);
double e = expected[i];
Assert.AreEqual(e, actual, 0.1);
}
}
public void LeukemiaExample_KaplanMeier()
{
// The following are times of remission (weeks) for 21 leukemia
// patients receiving control treatment (Table 1.1 of Cox & Oakes):
// http://www-personal.umich.edu/~yili/lect2notes.pdf
double[] t = { 1, 1, 2, 2, 3, 4, 4, 5, 5, 8, 8, 8, 8, 11, 11, 12, 12, 15, 17, 22, 23 };
var distribution = new EmpiricalHazardDistribution(SurvivalEstimator.KaplanMeier);
distribution.Fit(t, new EmpiricalHazardOptions {
Estimator = HazardEstimator.KaplanMeier
});
Assert.AreEqual(1, distribution.Survivals[0]);
Assert.AreEqual(0.905, distribution.Survivals[1], 1e-3);
Assert.AreEqual(0.809, distribution.Survivals[2], 1e-3);
Assert.AreEqual(0.762, distribution.Survivals[3], 1e-3);
/*
* http://statpages.org/prophaz2.html
* 1, 1
* 1, 1
* 2, 1
* 2, 1
* 3, 1
* 4, 1
* 4, 1
* 5, 1
* 5, 1
* 8, 1
* 8, 1
* 8, 1
* 8, 1
* 11, 1
* 11, 1
* 12, 1
* 12, 1
* 15, 1
* 17, 1
* 22, 1
* 23, 1
*/
}
public void KaplanMeierTest1()
{
// Example from
// http://sas-and-r.blogspot.fr/2010/05/example-738-kaplan-meier-survival.html
double[] times;
SurvivalOutcome[] censor;
CreateExample1(out times, out censor);
var distribution = new EmpiricalHazardDistribution(SurvivalEstimator.KaplanMeier);
Assert.AreEqual(SurvivalEstimator.KaplanMeier, distribution.Estimator);
distribution.Fit(times, new EmpiricalHazardOptions(HazardEstimator.KaplanMeier, censor));
int[] t = { 1, 2, 3, 4, 6, 8, 9, 12, 14, 20 };
double[] e = { 0.889, 0.833, 0.774, 0.714, 0.649, 0.577, 0.505, 0.421, 0.337, 0.168 };
double[] actual = t.ToDouble().Apply(distribution.ComplementaryDistributionFunction);
for (int i = 0; i < e.Length; i++)
Assert.AreEqual(e[i], actual[i], 1e-3);
// Assert.AreEqual(11.177, distribution.Mean);
Assert.AreEqual(12, distribution.Median, 1e-5);
}
public void LeukemiaExampleCensoring_KaplanMeier_FlemingHarrington()
{
// The following are times of remission (weeks) for 21 leukemia
// patients receiving control treatment (Table 1.1 of Cox & Oakes):
double[] t = { 6, 6, 6, 6, 7, 9, 10, 10, 11, 13, 16, 17, 19, 20, 22, 23, 25, 32, 32, 34, 35 };
int[] c = { 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0 };
var distribution = new EmpiricalHazardDistribution(SurvivalEstimator.FlemingHarrington);
distribution.Fit(t, new SurvivalOptions { Outcome = c.To<SurvivalOutcome[]>() });
int[] intervals = { 6, 7, 9, 10, 11, 13, 16, 17, 19, 20, 22, 23, 25, 32, 34, 35 };
double[] expected =
{
0.8571 , 0.8067, 0.8067, 0.7529, 0.7529, 0.6902,
0.6275, 0.6275, 0.6275, 0.6275, 0.5378, 0.4482,
0.4482, 0.4482, 0.4482, 0.4482
};
for (int i = 0; i < intervals.Length; i++)
{
double x = intervals[i];
double actual = distribution.ComplementaryDistributionFunction(x);
double e = expected[i];
Assert.AreEqual(e, actual, 0.1);
}
}
public void LeukemiaExample_KaplanMeier()
{
// The following are times of remission (weeks) for 21 leukemia
// patients receiving control treatment (Table 1.1 of Cox & Oakes):
// http://www-personal.umich.edu/~yili/lect2notes.pdf
double[] t = { 1, 1, 2, 2, 3, 4, 4, 5, 5, 8, 8, 8, 8, 11, 11, 12, 12, 15, 17, 22, 23 };
var distribution = new EmpiricalHazardDistribution(SurvivalEstimator.KaplanMeier);
distribution.Fit(t, new EmpiricalHazardOptions { Estimator = HazardEstimator.KaplanMeier });
Assert.AreEqual(1, distribution.Survivals[0]);
Assert.AreEqual(0.905, distribution.Survivals[1], 1e-3);
Assert.AreEqual(0.809, distribution.Survivals[2], 1e-3);
Assert.AreEqual(0.762, distribution.Survivals[3], 1e-3);
/*
http://statpages.org/prophaz2.html
1, 1
1, 1
2, 1
2, 1
3, 1
4, 1
4, 1
5, 1
5, 1
8, 1
8, 1
8, 1
8, 1
11, 1
11, 1
12, 1
12, 1
15, 1
17, 1
22, 1
23, 1
*/
}
