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Components descriptive analysis

Source: R/compdesc.R
compdesc.Rd

The function performs a descriptive analysis regarding the frequency of the components in the network meta-analysis model.

Usage

compdesc(model, sep = "+", heatmap = TRUE, percentage = TRUE, digits = 2)

Arguments

model

An object of class netmeta.

sep

A single character that defines the separator between interventions components.

heatmap

logical. If TRUE a heat matrix of the component's frequency is plotted.

percentage

logical. If TRUE combinations' percentages are printed as a number instead of fraction value in the heatmap.

digits

A single integer value that specifies the percentages' decimal places in the heatmap.

Value

A list containing three items

crosstable

A cross-table containing the frequency of the components. Each cell represents the number of arms where the corresponding component combination was observed.

frequency

A data.frame that contains the component's frequency. Columns

  • Component denotes the name of each component

  • Frequency denotes the number of arms where the component was observed

  • A denotes the number of studies in which the corresponding component was included in all arms

  • A_percent denotes the percentage of studies in which the corresponding component was included in all arms

  • B denotes the number of studies in which the corresponding component was included in at least one arm

  • B_percent denotes the percentage of studies in which the corresponding component was included in at least one arm

  • C denotes the number of studies in which the corresponding component was not included in any arm

  • C_percent denotes the percentage of studies in which the corresponding component was not included in any arm

  • A.B denotes the ratio of columns A and B.

heatmat

An object of class ggplot that visualizes item crosstable. Diagonal elements refer to the components and in parentheses the proportion of study arms including that component is provided, while off-diagonal elements to the frequency of component’s combinations and in parentheses the proportion of study arms with both components out of those study arms that have the component in the row is provided. Also, the intensity of the color is proportional to the relative frequency of the component combination.

Note

The function can be applied only in network meta-analysis models that contain multi-component interventions.

Examples

data(nmaMACE)
compdesc(model = nmaMACE)
#> $crosstable
#>     A  B  C  D G E UC
#> A  17  9  9  5 0 2  0
#> B   9 18  7  5 1 2  0
#> C   9  7 15  4 0 1  0
#> D   5  5  4 11 0 0  0
#> G   0  1  0  0 1 0  0
#> E   2  2  1  0 0 3  0
#> UC  0  0  0  0 0 0 15
#> 
#> $frequency
#>    Component Frequency A  A_percent  B  B_percent  C C_percent       A.B
#> A          A        17 2 0.09090909 11 0.50000000 11 0.5000000 0.1818182
#> B          B        18 3 0.13636364 13 0.59090909  9 0.4090909 0.2307692
#> C          C        15 2 0.09090909 11 0.50000000 11 0.5000000 0.1818182
#> D          D        11 1 0.04545455  9 0.40909091 13 0.5909091 0.1111111
#> G          G         1 0 0.00000000  1 0.04545455 21 0.9545455 0.0000000
#> E          E         3 0 0.00000000  3 0.13636364 19 0.8636364 0.0000000
#> UC        UC        15 0 0.00000000 15 0.68181818  7 0.3181818 0.0000000
#> 
#> $heatmat

#>