MFh: Identify ranks for use when evaluating MF for nested...

In ABS-dev/MF: Mitigated Fraction

Identify ranks for use when evaluating MF for nested hierarchy.

Description

Identify ranks for use when evaluating MF for nested hierarchy.

Usage

MFh(formula, data, compare = c("con", "vac"))

Arguments

formula	Formula of the form y ~ x + a/b/c, where y is a continuous response, x is a factor with two levels of treatment, and a/b/c are vgrouping variables corresponding to the clusters. Nesting is assumed to be in order, left to right, highest to lowest. So a single level of "a" will contain multiple levels of "b" and a single level of "b" will contain multiple levels of "c".
data	a data.frame or tibble with the variables specified in formula. Additional variables will be ignored.
compare	Text vector stating the factor levels - compare[1] is the control or reference group to which compare[2] is compared.

Value

A mfhierdata object, which is a list of three items.

• coreTbl A dplyr::tibble with one row for each unique core level showing values for:

  • con_n & vac_n: counts of observations for each treatment level in the core level.

  • con_medResp & vac_medResp: median of the y continuous response for each treatment level.

  • n1n2: product of the counts, con_n \times vac_n.

  • w: Wilcoxon statistic

  • u: Mann-Whitney statistic

• data: A dplyr::tibble of the restructured input data used for calculations.

• compare: The compare variables as input by user.

• formula: The formula as input by user.

Note

Core variable is the variable corresponding to the lowest nodes of the hierarchial tree. Nest variables are those above the core.

Author(s)

MF-package

See Also

MFnest for calculation of MF for nest, core and all variables. mfhierdata for returned object. MFClusHier for a wrapper.

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))
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)
aCore
#  A tibble: 12 x 10
#     room   pen   litter    con_medResp con_n     w vac_medResp vac_n  n1n2
#     <chr>  <chr> <chr>           <dbl> <dbl> <dbl>       <dbl> <dbl> <dbl>
#   1 Room W Pen A Litter 11        8.24     2     7        5.13     2     4
#   2 Room W Pen A Litter 12        4.91     2     5        3.81     2     4
#   3 Room W Pen B Litter 13        8.10     2     7        5.23     2     4
#   4 Room W Pen B Litter 14        8.11     2     7        5.59     2     4
#   5 Room W Pen C Litter 15        8.09     2     7        5.26     2     4
#   6 Room W Pen C Litter 16        6.77     2     7        4.50     2     4
#   7 Room Z Pen D Litter 17        5.58     2     7        4.26     2     4
#   8 Room Z Pen D Litter 18        7.44     2     6        6.33     2     4
#   9 Room Z Pen E Litter 19        7.98     2     7        4.58     2     4
#  10 Room Z Pen E Litter 20        6.78     2     7        4.86     2     4
#  11 Room Z Pen F Litter 21        6.82     2     7        5.36     2     4
#  12 Room Z Pen F Litter 22        7.27     2     7        5.13     2     4

ABS-dev/MF documentation built on Sept. 19, 2024, 10:30 a.m.