srktie_m {EQUIVNONINF} | R Documentation |
Analogue of srktie_d for settings where the distribution of intraindividual differences is concentrated on a finite lattice
Description
Analogue of the function srktie_d tailored for settings where the distribution of the within-subject differences is concentrated on a finite lattice. For details see Wellek S (2010) Testing statistical hypotheses of equivalence and noninferiority. Second edition, pp.112-3.
Usage
srktie_m(n,alpha,eps1,eps2,w,d)
Arguments
n |
sample size |
alpha |
significance level |
eps1 |
absolute value of the left-hand limit of the hypothetical equivalence range for
|
eps2 |
right-hand limit of the hypothetical equivalence range for |
w |
span of the lattice in which the intraindividual differences take their values |
d |
row vector with the intraindividual differences for all |
Details
Notation: and
stands for the functional defined by
and
, respectively,
with
and
as the intraindividual differences observed in two individuals
independently selected from the underlying bivariate population.
Value
n |
sample size |
alpha |
significance level |
eps1 |
absolute value of the left-hand limit of the hypothetical equivalence range for
|
eps2 |
right-hand limit of the hypothetical equivalence range for |
w |
span of the lattice in which the intraindividual differences take their values |
U_pl |
observed value of the |
U_0 |
observed value of the |
UAS_PL |
observed value of |
TAUHAS |
square root of the estimated asymtotic variance of |
CRIT |
upper critical bound to |
REJ |
indicator of a positive [=1] vs negative [=0] rejection decision to be taken with the data under analysis |
Author(s)
Stefan Wellek <stefan.wellek@zi-mannheim.de>
Peter Ziegler <peter.ziegler@zi-mannheim.de>
References
Wellek S: Testing statistical hypotheses of equivalence and noninferiority. Second edition. Boca Raton: Chapman & Hall/CRC Press, 2010, pp. 112-114.
Examples
d <- c(0.8,0.2,0.0,-0.1,-0.3,0.3,-0.1,0.4,0.6,0.2,0.0,-0.2,-0.3,0.0,0.1,0.3,-0.3,
0.1,-0.2,-0.5,0.2,-0.1,0.2,-0.1)
srktie_m(24,0.05,0.2602,0.2602,0.1,d)