MFnest: Summations to calculate the MF for nested data from a rank...
In ABS-dev/MF: Mitigated Fraction
MFnest R Documentation
Summations to calculate the MF for nested data from a rank table.
Description
Summations to calculate the MF for nested data from a rank table.
Usage
MFnest(Y, which.factor = "All")
Arguments
Y
rank table (tibble or data.frame), structured as $coreTbl
output from MFh or returned object from MFh().
which.factor
one or more grouping variable(s) of interest. This can be
any of the core or nest variables from the data set. If none or All
is specified, a summary MF will be calculated for the whole tree.
Value
A tibble with each unique level of a variable as a row. Other values
include:
MFMitigated fraction for the particular level of the
variable in this row.
N1N2Sum of the n1n2 variable in $coreTbl field
of mfhierdata object output by MFh for this
particular variable-level combination.
USum of u variable in $coreTbl field of
mfhierdata object output by MFh for this
particular variable-level combination.
_NSum of the _n variable in $coreTbl field of
mfhierdata object output by MFh for this
particular variable-level combination.
_medRespMedian of observed responses for each comparison
group for this particular variable-level combination.
Note
Core variable is the variable corresponding to the lowest nodes of the
hierarchial tree. Nest variables are those above the core. All refers to a
summary of the entire tree.
Author(s)
MF-package
See Also
MFh
Examples
a <- data.frame(
room = paste('Room', rep(c('W','Z'), each=24)),
pen = paste('Pen', rep(LETTERS[1:6], each=8)),
litter = paste('Litter', rep(11:22, each=4)),
tx = rep(rep(c('vac','con'), each=2), 12),
stringsAsFactors = FALSE
)
set.seed(76153)
a$lung[a$tx=='vac'] <- rnorm(24, 5, 1.3)
a$lung[a$tx=='con'] <- rnorm(24, 7, 1.3)
aCore <- MFh(lung ~ tx + room / pen / litter, a)
MFnest(aCore)
# # A tibble: 1 x 9
# variable level MF N1N2 U con_N vac_N con_medResp vac_medResp
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 All All 0.875 48 45 24 24 7.24 4.91
MFnest(aCore$coreTbl)
# Skipping median summary, no response data provided.
# # A tibble: 1 x 7
# variable level MF N1N2 U con_N vac_N
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 All All 0.875 48 45 24 24
MFnest(aCore, 'room')
# # A tibble: 2 x 9
# variable level MF N1N2 U con_N vac_N con_medResp vac_medResp
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 room Room W 0.833 24 22 12 12 7.79 4.85
# 2 room Room Z 0.917 24 23 12 12 6.71 4.98
MFnest(aCore, 'pen')
# Complete separation observed for variable(s): pen
# # A tibble: 6 x 9
# variable level MF N1N2 U con_N vac_N con_medResp vac_medResp
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 pen Pen A 0.5 8 6 4 4 6.79 4.24
# 2 pen Pen B 1 8 8 4 4 8.11 5.59
# 3 pen Pen C 1 8 8 4 4 7.69 4.85
# 4 pen Pen D 0.75 8 7 4 4 6.10 4.98
# 5 pen Pen E 1 8 8 4 4 6.86 4.86
# 6 pen Pen F 1 8 8 4 4 6.88 5.13
MFnest(aCore, c('All', 'litter'))
# Complete separation observed for variable(s): litter
# # A tibble: 13 x 9
# variable level MF N1N2 U con_N vac_N con_medResp vac_medResp
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 All All 0.875 48 45 24 24 7.24 4.91
# 2 litter Litter 11 1 4 4 2 2 8.24 5.13
# 3 litter Litter 12 0 4 2 2 2 4.91 3.81
# 4 litter Litter 13 1 4 4 2 2 8.10 5.23
# 5 litter Litter 14 1 4 4 2 2 8.11 5.59
# 6 litter Litter 15 1 4 4 2 2 8.09 5.26
# 7 litter Litter 16 1 4 4 2 2 6.77 4.50
# 8 litter Litter 17 1 4 4 2 2 5.58 4.26
# 9 litter Litter 18 0.5 4 3 2 2 7.44 6.33
# 10 litter Litter 19 1 4 4 2 2 7.98 4.58
# 11 litter Litter 20 1 4 4 2 2 6.78 4.86
# 12 litter Litter 21 1 4 4 2 2 6.82 5.36
# 13 litter Litter 22 1 4 4 2 2 7.27 5.13
MFnest(aCore, 'litter')
# Complete separation observed for variable(s): litter
# # A tibble: 12 x 9
# variable level MF N1N2 U con_N vac_N con_medResp vac_medResp
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 litter Litter 11 1 4 4 2 2 8.24 5.13
# 2 litter Litter 12 0 4 2 2 2 4.91 3.81
# 3 litter Litter 13 1 4 4 2 2 8.10 5.23
# 4 litter Litter 14 1 4 4 2 2 8.11 5.59
# 5 litter Litter 15 1 4 4 2 2 8.09 5.26
# 6 litter Litter 16 1 4 4 2 2 6.77 4.50
# 7 litter Litter 17 1 4 4 2 2 5.58 4.26
# 8 litter Litter 18 0.5 4 3 2 2 7.44 6.33
# 9 litter Litter 19 1 4 4 2 2 7.98 4.58
# 10 litter Litter 20 1 4 4 2 2 6.78 4.86
# 11 litter Litter 21 1 4 4 2 2 6.82 5.36
# 12 litter Litter 22 1 4 4 2 2 7.27 5.13
MFnest(aCore, c('room', 'pen', 'litter'))
# # A tibble: 20 x 9
# variable level MF N1N2 U con_N vac_N con_medResp vac_medResp
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 room Room W 0.833 24 22 12 12 7.79 4.85
# 2 room Room Z 0.917 24 23 12 12 6.71 4.98
# 3 pen Pen A 0.5 8 6 4 4 6.79 4.24
# 4 pen Pen B 1 8 8 4 4 8.11 5.59
# 5 pen Pen C 1 8 8 4 4 7.69 4.85
# 6 pen Pen D 0.75 8 7 4 4 6.10 4.98
# 7 pen Pen E 1 8 8 4 4 6.86 4.86
# 8 pen Pen F 1 8 8 4 4 6.88 5.13
# 9 litter Litter 11 1 4 4 2 2 8.24 5.13
# 10 litter Litter 12 0 4 2 2 2 4.91 3.81
# 11 litter Litter 13 1 4 4 2 2 8.10 5.23
# 12 litter Litter 14 1 4 4 2 2 8.11 5.59
# 13 litter Litter 15 1 4 4 2 2 8.09 5.26
# 14 litter Litter 16 1 4 4 2 2 6.77 4.50
# 15 litter Litter 17 1 4 4 2 2 5.58 4.26
# 16 litter Litter 18 0.5 4 3 2 2 7.44 6.33
# 17 litter Litter 19 1 4 4 2 2 7.98 4.58
# 18 litter Litter 20 1 4 4 2 2 6.78 4.86
# 19 litter Litter 21 1 4 4 2 2 6.82 5.36
# 20 litter Litter 22 1 4 4 2 2 7.27 5.13
ABS-dev/MF documentation built on April 21, 2024, 5:55 p.m.
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| MFnest | R Documentation |
Summations to calculate the MF for nested data from a rank table.
Description
Summations to calculate the MF for nested data from a rank table.
Usage
MFnest(Y, which.factor = "All")
Arguments
Y |
rank table (tibble or data.frame), structured as |
which.factor |
one or more grouping variable(s) of interest. This can be
any of the core or nest variables from the data set. If none or |
Value
A tibble with each unique level of a variable as a row. Other values
include:
MFMitigated fraction for the particular level of the variable in this row.
N1N2Sum of the
n1n2variable in$coreTblfield ofmfhierdataobject output byMFhfor this particular variable-level combination.USum of u variable in
$coreTblfield ofmfhierdataobject output byMFhfor this particular variable-level combination._NSum of the
_nvariable in$coreTblfield ofmfhierdataobject output byMFhfor this particular variable-level combination._medRespMedian of observed responses for each comparison group for this particular variable-level combination.
Note
Core variable is the variable corresponding to the lowest nodes of the hierarchial tree. Nest variables are those above the core. All refers to a summary of the entire tree.
Author(s)
MF-package
See Also
MFh
Examples
a <- data.frame(
room = paste('Room', rep(c('W','Z'), each=24)),
pen = paste('Pen', rep(LETTERS[1:6], each=8)),
litter = paste('Litter', rep(11:22, each=4)),
tx = rep(rep(c('vac','con'), each=2), 12),
stringsAsFactors = FALSE
)
set.seed(76153)
a$lung[a$tx=='vac'] <- rnorm(24, 5, 1.3)
a$lung[a$tx=='con'] <- rnorm(24, 7, 1.3)
aCore <- MFh(lung ~ tx + room / pen / litter, a)
MFnest(aCore)
# # A tibble: 1 x 9
# variable level MF N1N2 U con_N vac_N con_medResp vac_medResp
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 All All 0.875 48 45 24 24 7.24 4.91
MFnest(aCore$coreTbl)
# Skipping median summary, no response data provided.
# # A tibble: 1 x 7
# variable level MF N1N2 U con_N vac_N
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 All All 0.875 48 45 24 24
MFnest(aCore, 'room')
# # A tibble: 2 x 9
# variable level MF N1N2 U con_N vac_N con_medResp vac_medResp
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 room Room W 0.833 24 22 12 12 7.79 4.85
# 2 room Room Z 0.917 24 23 12 12 6.71 4.98
MFnest(aCore, 'pen')
# Complete separation observed for variable(s): pen
# # A tibble: 6 x 9
# variable level MF N1N2 U con_N vac_N con_medResp vac_medResp
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 pen Pen A 0.5 8 6 4 4 6.79 4.24
# 2 pen Pen B 1 8 8 4 4 8.11 5.59
# 3 pen Pen C 1 8 8 4 4 7.69 4.85
# 4 pen Pen D 0.75 8 7 4 4 6.10 4.98
# 5 pen Pen E 1 8 8 4 4 6.86 4.86
# 6 pen Pen F 1 8 8 4 4 6.88 5.13
MFnest(aCore, c('All', 'litter'))
# Complete separation observed for variable(s): litter
# # A tibble: 13 x 9
# variable level MF N1N2 U con_N vac_N con_medResp vac_medResp
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 All All 0.875 48 45 24 24 7.24 4.91
# 2 litter Litter 11 1 4 4 2 2 8.24 5.13
# 3 litter Litter 12 0 4 2 2 2 4.91 3.81
# 4 litter Litter 13 1 4 4 2 2 8.10 5.23
# 5 litter Litter 14 1 4 4 2 2 8.11 5.59
# 6 litter Litter 15 1 4 4 2 2 8.09 5.26
# 7 litter Litter 16 1 4 4 2 2 6.77 4.50
# 8 litter Litter 17 1 4 4 2 2 5.58 4.26
# 9 litter Litter 18 0.5 4 3 2 2 7.44 6.33
# 10 litter Litter 19 1 4 4 2 2 7.98 4.58
# 11 litter Litter 20 1 4 4 2 2 6.78 4.86
# 12 litter Litter 21 1 4 4 2 2 6.82 5.36
# 13 litter Litter 22 1 4 4 2 2 7.27 5.13
MFnest(aCore, 'litter')
# Complete separation observed for variable(s): litter
# # A tibble: 12 x 9
# variable level MF N1N2 U con_N vac_N con_medResp vac_medResp
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 litter Litter 11 1 4 4 2 2 8.24 5.13
# 2 litter Litter 12 0 4 2 2 2 4.91 3.81
# 3 litter Litter 13 1 4 4 2 2 8.10 5.23
# 4 litter Litter 14 1 4 4 2 2 8.11 5.59
# 5 litter Litter 15 1 4 4 2 2 8.09 5.26
# 6 litter Litter 16 1 4 4 2 2 6.77 4.50
# 7 litter Litter 17 1 4 4 2 2 5.58 4.26
# 8 litter Litter 18 0.5 4 3 2 2 7.44 6.33
# 9 litter Litter 19 1 4 4 2 2 7.98 4.58
# 10 litter Litter 20 1 4 4 2 2 6.78 4.86
# 11 litter Litter 21 1 4 4 2 2 6.82 5.36
# 12 litter Litter 22 1 4 4 2 2 7.27 5.13
MFnest(aCore, c('room', 'pen', 'litter'))
# # A tibble: 20 x 9
# variable level MF N1N2 U con_N vac_N con_medResp vac_medResp
# <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 room Room W 0.833 24 22 12 12 7.79 4.85
# 2 room Room Z 0.917 24 23 12 12 6.71 4.98
# 3 pen Pen A 0.5 8 6 4 4 6.79 4.24
# 4 pen Pen B 1 8 8 4 4 8.11 5.59
# 5 pen Pen C 1 8 8 4 4 7.69 4.85
# 6 pen Pen D 0.75 8 7 4 4 6.10 4.98
# 7 pen Pen E 1 8 8 4 4 6.86 4.86
# 8 pen Pen F 1 8 8 4 4 6.88 5.13
# 9 litter Litter 11 1 4 4 2 2 8.24 5.13
# 10 litter Litter 12 0 4 2 2 2 4.91 3.81
# 11 litter Litter 13 1 4 4 2 2 8.10 5.23
# 12 litter Litter 14 1 4 4 2 2 8.11 5.59
# 13 litter Litter 15 1 4 4 2 2 8.09 5.26
# 14 litter Litter 16 1 4 4 2 2 6.77 4.50
# 15 litter Litter 17 1 4 4 2 2 5.58 4.26
# 16 litter Litter 18 0.5 4 3 2 2 7.44 6.33
# 17 litter Litter 19 1 4 4 2 2 7.98 4.58
# 18 litter Litter 20 1 4 4 2 2 6.78 4.86
# 19 litter Litter 21 1 4 4 2 2 6.82 5.36
# 20 litter Litter 22 1 4 4 2 2 7.27 5.13
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