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central_group

Source: R/central_group.R
central_group.Rd

Function to compare means or medians in different groups from complex survey data. It produces a table, a graphic and a statistical test.

Usage

central_group(
  data,
  group,
  quanti_exp,
  type,
  group.fill = NULL,
  facet = NULL,
  filter_exp = NULL,
  ...,
  na.rm.group = T,
  na.rm.facet = T,
  total = TRUE,
  reorder = F,
  show_ci = T,
  show_n = FALSE,
  show_value = TRUE,
  show_labs = TRUE,
  total_name = NULL,
  digits = 0,
  unit = "",
  dec = ",",
  pal = NULL,
  direction = 1,
  desaturate = 0,
  lighten = 0,
  darken = 0,
  dodge = 0.9,
  font = "Roboto",
  wrap_width_y = 25,
  wrap_width_leg = 25,
  legend_ncol = 4,
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  legend_lab = NULL,
  caption = NULL,
  lang = "fr",
  theme = NULL,
  export_path = NULL
)

median_group(..., type = "median")

mean_group(..., type = "mean")

Arguments

data

A dataframe or an object from the survey package or an object from the srvyr package.

group

A variable defining groups to be compared.

quanti_exp

An expression that define the variable from which the mean/median is computed.

type

"mean" to compute mean by group ; "median" to compute median by group.

group.fill

A variable defining a second variable of groups to be compared.

facet

A variable defining the faceting group.

filter_exp

An expression that filters the data, preserving the design.

...

All options possible in as_survey_design in srvyr package.

na.rm.group

TRUE if you want to remove observations with NA on the group variable or NA on the facet variable, if applicable. FALSE if you want to create a group with the NA value for the group variable and a facet with the NA value for the facet variable. NA in the variables included in quanti_exp are not affected in this argument. All the observation with a NA in the variables included in quanti_exp are always excluded. Default is TRUE.

na.rm.facet

TRUE if you want to remove observations with NA on the group variable or NA on the facet variable. FALSE if you want to create a group with the NA value for the group variable and a facet with the NA value for the facet variable. NA in the variables included in prop_exp are not affected in this argument. All the observation with a NA in the variables included in prop_exp are excluded.

total

TRUE if you want to calculate a total, FALSE if you don't. The default is TRUE

reorder

TRUE if you want to reorder the groups according to the mean/median. NA value, in case if na.rm.group = FALSE, is not included in the reorder.

show_ci

TRUE if you want to show the error bars on the graphic. FALSE if you do not want to show the error bars. Default is TRUE.

show_n

TRUE if you want to show on the graphic the number of individuals in the sample in each group. FALSE if you do not want to show this number. Default is FALSE.

show_value

TRUE if you want to show the mean/median of each group on the graphic. FALSE if you do not want to show the mean/median. Default is TRUE.

show_labs

TRUE if you want to show axes, titles and caption labels. FALSE if you do not want to show any label on axes and titles. Default is TRUE.

total_name

Name of the total bar on the graphic. Default is Total.

digits

Numbers of digits showed on the value labels on the graphic. Default is 0.

unit

Unit showed on the graphic. Default is no unit.

dec

Decimal mark shown on the graphic. Default is ",".

pal

If group.fill is empty, pal must be a vector containing a single color to define the color of the bars. If a variable is specified in group.fill, pal is the color palette used on the graph to differentiate its different modalities. Palettes from the MetBrewer, MoMAColors and PrettyCols packages are available. The NA bar, if na.rm.group = FALSE, and the total bar are always in gray.

direction

Direction of the palette color. Default is 1. The opposite direction is -1.

desaturate

Numeric specifying the amount of desaturation where 1 corresponds to complete desaturation, 0 to no desaturation, and values in between to partial desaturation.

lighten

Numeric specifying the amount of lightening. Negative numbers cause darkening.

darken

Numeric specifying the amount of lightening. Negative numbers cause lightening.

dodge

Width of the bar, between 0 and 1.Default is 0.9.

font

Font used in the graphic. See load_and_active_fonts() for available fonts.

wrap_width_y

Number of characters before going to the line in the labels of the groups. Default is 25.

wrap_width_leg

Number of characters before going to the line for the labels of the categories of group.fill. Default is 25.

legend_ncol

Number of colomns in the legend. Default is 4.

title

Title of the graphic.

subtitle

Subtitle of the graphic.

xlab

X label on the graphic. As coord_flip() is used in the graphic, xlab refers to the X label on the graphic, after the coord_flip(), and not to the x variable in the data. If xlab = NULL, X label on the graphic will be "Moyenne : " + quanti_exp or "Medianne : " + quanti_exp. To show no X label, use xlab = "".

ylab

Y label on the graphic. As coord_flip() is used in the graphic, ylab refers to the Y label on the graphic, after the coord_flip(), and not to the y variable in the data. If ylab = NULL, Y label on the graphic will be group. To show no Y label, use ylab = "".

legend_lab

Legend (fill) label on the graphic. If legend_lab = NULL, legend label on the graphic will be group.fill. To show no legend label, use legend_lab = "".

caption

Caption of the graphic.

lang

The language of the indications on the chart. Possibilities: "fr", "nl", "en". Default is "fr".

theme

Theme od te graphic. IWEPS adds y axis lines and ticks.

export_path

Path to export the results in an xlsx file. The file includes three sheets : the table, the graphic and the statistical test.

Value

A list that contains a table, a graphic and a statistical test

Examples

# Loading of data
data(eusilc, package = "laeken")

# Creation of age categories
eusilc$age_cat <- cut(eusilc$age,
breaks = 6,
include.lowest = TRUE)

# Calculation of income means by age category with fonctionr, taking sample design into account
eusilc_mean <- mean_group(
  eusilc,
  group = age_cat,
  quanti_exp = eqIncome / 12,
  strata = db040,
  ids = db030,
  weight = rb050,
  title = "Mean of equivalised income in household by age of individuals",
  subtitle = "Example with austrian SILC data from 'laeken' package"
  )
#> Input: data.frame
#> Sampling design -> ids:  db030, strata:  db040, weights:  rb050
#> Variable(s) detectee(s) dans quanti_exp : eqIncome
#> 0 lignes supprimees avec valeur(s) manquante(s) pour le(s) variable(s) de quanti_exp

# Results in graph form
eusilc_mean$graph


# Results in table format
eusilc_mean$tab
#> # A tibble: 7 × 8
#>   age_cat      mean mean_low mean_upp n_sample n_weighted n_weighted_low
#>   <fct>       <dbl>    <dbl>    <dbl>    <int>      <dbl>          <dbl>
#> 1 [-1.1,15.3] 1444.    1409.    1479.     2720   1424958.       1358818.
#> 2 (15.3,31.7] 1607.    1571.    1643.     2944   1612502.       1549489.
#> 3 (31.7,48]   1703.    1669.    1737.     4025   2230581.       2163723.
#> 4 (48,64.3]   1889.    1843.    1935.     2817   1578046.       1517273.
#> 5 (64.3,80.7] 1611.    1561.    1662.     1847   1053098.       1001605.
#> 6 (80.7,97.1] 1545.    1467.    1622.      474    283037.        256754.
#> 7 Total       1658.    1635.    1681.    14827   8182222        8079226.
#> # ℹ 1 more variable: n_weighted_upp <dbl>