man/examples/examples_get_sim_lim.R

In disprofas: Non-Parametric Dissolution Profile Analysis

# Dissolution data of one reference batch and one test batch of n = 6
# tablets each:
str(dip1)

# 'data.frame':	12 obs. of  10 variables:
# $ type  : Factor w/ 2 levels "R","T": 1 1 1 1 1 1 2 2 2 2 ...
# $ tablet: Factor w/ 6 levels "1","2","3","4",..: 1 2 3 4 5 6 1 2 3 4 ...
# $ t.5   : num  42.1 44.2 45.6 48.5 50.5 ...
# $ t.10  : num  59.9 60.2 55.8 60.4 61.8 ...
# $ t.15  : num  65.6 67.2 65.6 66.5 69.1 ...
# $ t.20  : num  71.8 70.8 70.5 73.1 72.8 ...
# $ t.30  : num  77.8 76.1 76.9 78.5 79 ...
# $ t.60  : num  85.7 83.3 83.9 85 86.9 ...
# $ t.90  : num  93.1 88 86.8 88 89.7 ...
# $ t.120 : num  94.2 89.6 90.1 93.4 90.8 ...

# Estimation of the parameters for Hotelling's two-sample T2 statistic
# (for small samples)
hs <- get_hotellings(m1 = as.matrix(dip1[dip1$type == "R", c("t.15", "t.90")]),
                    m2 = as.matrix(dip1[dip1$type == "T", c("t.15", "t.90")]),
                    signif = 0.1)

# Estimation of the similarity limit in terms of the "Multivariate Statistical
# Distance" (MSD)for a "maximum tolerable average difference" (mtad) of 10
res <- get_sim_lim(mtad = 15, hs)

# Expected results in res
#            DM              df1              df2            alpha
#  1.044045e+01     2.000000e+00     9.000000e+00     1.000000e-01
#             K                k               T2                F
#  1.350000e+00     3.000000e+00     3.270089e+02     1.471540e+02
# ncp.Hoffelder           F.crit F.crit.Hoffelder              p.F
#  2.782556e+02     3.006452e+00     8.357064e+01     1.335407e-07
# p.F.Hoffelder             MTAD        Sim.Limit
#  4.822832e-01     1.500000e+01     9.630777e+00