EDNE.EQ {EDNE.EQ} | R Documentation |
The EDNE-test for equivalence
Description
The function EDNE.EQ()
implements the EDNE-test for equivalence according to Hoffelder et al. (2015). It is a multivariate two-sample equivalence procedure. Distance measure of the test is the Euclidean distance.
Usage
EDNE.EQ(X, Y, eq_margin, alpha = 0.05, print.results = TRUE)
Arguments
X |
numeric data matrix of the first sample (REF). The rows of |
Y |
numeric data matrix of the second sample (TEST). The rows of |
eq_margin |
numeric (>0). The equivalence margin of the test. |
alpha |
numeric (0< |
print.results |
logical; if TRUE (default) summary statistics and test results are printed in the output. If NO no output is created |
Details
This function implements the EDNE-test for equivalence. Distance measure of the test is the Euclidean distance. The test is an asymptotically valid test for the family of distributions fulfilling the assumptions of the multivariate central limit theorem (for further details see Hoffelder et al.,2015).
Value
a data frame; three columns containing the results of the test
p.value |
numeric; the p-value of the equivalence test according to Hoffelder et al. (2015) |
testresult.num |
numeric; 0 (null hypothesis of nonequivalence not rejected) or 1 (null hypothesis of nonequivalence rejected, decision in favor of equivalence) |
testresult.text |
character; test result of the test in text mode |
Author(s)
Thomas Hoffelder <thomas.hoffelder at boehringer-ingelheim.com>
References
Hoffelder, T., Goessl, R., Wellek, S. (2015). Multivariate Equivalence Tests for Use in Pharmaceutical Development. Journal of Biopharmaceutical Statistics, 25:3, 417-437. URL: http://dx.doi.org/10.1080/10543406.2014.920344
Examples
# A recalculation of the three-dimensional EDNE example evaluation
# in Hoffelder et al. (2015) can be done with the following code:
data(ex_data_JoBS)
REF_JoBS <- cbind(ex_data_JoBS[ which(ex_data_JoBS$Group=='REF'), ]
[c("Diss_15_min","Diss_20_min","Diss_25_min")])
TEST_JoBS <- cbind(ex_data_JoBS[ which(ex_data_JoBS$Group=='TEST'), ]
[c("Diss_15_min","Diss_20_min","Diss_25_min")])
equivalence_margin_JoBS <- 297
test_EDNE_JoBS <- EDNE.EQ(X=REF_JoBS
, Y=TEST_JoBS
, eq_margin=equivalence_margin_JoBS
, print.results = TRUE)