summary.mimcr: Summary of MIMCR estimation

In disprofas: Non-Parametric Dissolution Profile Analysis

Description

This is a method for the function summary() for objects of class ‘mimcr’.

Usage

## S3 method for class 'mimcr'
summary(object, ...)

Arguments

object	An object of class ‘mimcr’ returned by the mimcr() function.
...	Further arguments passed to or from other methods or arguments that can be passed down to the formatC() function.

Details

The most relevant information in an ‘mimcr’ object is printed.

Value

The ‘mimcr’ object passed to the object parameter is returned invisibly.

See Also

mimcr, formatC, methods.

Examples

# 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 ...

# Assessment of data by aid of the mimcr() function
res1 <- mimcr(data = dip1, tcol = 3:10, grouping = "type")

# Summary of the assessment
summary(res1)

# Results of Model-Independent Multivariate Confidence Region (MIMCR)
# approach to assess equivalence of highly variable in-vitro
# dissolution profiles of two drug product formulations
#
# Did the Newton-Raphson search converge? Yes
#
# Parameters (general):
#   Significance level:                 0.05
# Degrees of freedom (1):               7
# Degrees of freedom (2):               4
# Mahalanobis distance (MD):            25.72
# (F) scaling factor K:                 0.1714
# (MD) scaling factor k:                3
# Hotelling's T2:                       1984
#
# Parameters specific for Tsong (1996) approach:
# Maximum tolerable average difference: 10
# Similarity limit:                     11.33
# Observed upper limit:                 31.68
#
# Parameters specific for Hoffelder (2016) approach:
# Noncentrality parameter:              385
# Critial F (Hoffelder):                23.16
# Probability p (Hoffelder):            0.7402
#
# Conclusions:
#       Tsong (1996):  Dissimilar
#   Hoffelder (2016):  Dissimilar

# Taking only the 15 and 90 minutes testing points into account produces a
# warning because profiles should comprise a minimum of three testing points.
res2 <- mimcr(data = dip1, tcol = c(5, 9), grouping = "type", mtad = 15,
              signif = 0.1)
summary(res2)

# Warning:
#   In mimcr(data = dip1, tcol = c(5, 9), grouping = "type", mtad = 15,  :
# The profiles should comprise a minimum of 3 time points. The actual profiles
# comprise 2 points only.

# Results of Model-Independent Multivariate Confidence Region (MIMCR)
# approach to assess equivalence of highly variable in-vitro
# dissolution profiles of two drug product formulations
#
# Did the Newton-Raphson search converge? Yes
#
# Parameters (general):
#   Significance level:                 0.1
# Degrees of freedom (1):               2
# Degrees of freedom (2):               9
# Mahalanobis distance (MD):            10.44
# (F) scaling factor K:                 1.35
# (MD) scaling factor k:                3
# Hotelling's T2:                       327
#
# Parameters specific for Tsong (1996) approach:
# Maximum tolerable average difference: 15
# Similarity limit:                     9.631
# Observed upper limit:                 11.93
#
# Parameters specific for Hoffelder (2016) approach:
# Noncentrality parameter:              278.3
# Critial F (Hoffelder):                83.57
# Probability p (Hoffelder):            0.4823
#
# Conclusions:
#       Tsong (1996):  Dissimilar
#   Hoffelder (2016):  Dissimilar

# Dissolution data  of one reference batch and one test batch of n = 12
# capsules each:
str(dip3)

# 'data.frame':	24 obs. of  6 variables:
# $ cap  : Factor w/ 12 levels "1","2","3","4",..: 1 2 3 4 5 6 7 8 9 10 ...
# $ batch: Factor w/ 2 levels "blue","white": 2 2 2 2 2 2 2 2 2 2 ...
# $ type : Factor w/ 2 levels "ref","test": 1 1 1 1 1 1 1 1 1 1 ...
# $ x.15 : num  49 15 56 57 6 62 23 11 9 42 ...
# $ x.20 : num  86 59 84 87 58 90 71 64 61 81 ...
# $ x.25 : num  98 96 96 99 90 97 97 92 88 96 ...

# A successful comparison:
res3 <- mimcr(data = dip3, tcol = 4:6, grouping = "batch")
summary(res3)

# Results of Model-Independent Multivariate Confidence Region (MIMCR)
# approach to assess equivalence of highly variable in-vitro
# dissolution profiles of two drug product formulations
#
# Did the Newton-Raphson search converge? Yes
#
# Parameters (general):
#   Significance level:                 0.05
# Degrees of freedom (1):               3
# Degrees of freedom (2):               20
# Mahalanobis distance (MD):            0.2384
# (F) scaling factor K:                 1.818
# (MD) scaling factor k:                6
# Hotelling's T2:                       0.341
#
# Parameters specific for Tsong (1996) approach:
# Maximum tolerable average difference: 10
# Similarity limit:                     2.248
# Observed upper limit:                 1.544
#
# Parameters specific for Hoffelder (2016) approach:
# Noncentrality parameter:              30.32
# Critial F (Hoffelder):                4.899
# Probability p (Hoffelder):            2.891e-08
#
# Conclusions:
#       Tsong (1996):  Similar
#   Hoffelder (2016):  Similar

disprofas documentation built on Dec. 8, 2021, 5:10 p.m.