sjmisc (version 2.5.0)

split_var: Split numeric variables into smaller groups

Description

Recode numeric variables into equal sized groups, i.e. a variable is cut into a smaller number of groups at specific cut points.

Usage

split_var(x, ..., groupcount, as.num = FALSE, val.labels = NULL,
  var.label = NULL, inclusive = FALSE, append = FALSE, suffix = "_g")

Arguments

x

A vector or data frame.

...

Optional, unquoted names of variables that should be selected for further processing. Required, if x is a data frame (and no vector) and only selected variables from x should be processed. You may also use functions like : or dplyr's select_helpers. See 'Examples' or package-vignette.

groupcount

The new number of groups that x should be split into.

as.num

Logical, if TRUE, return value will be numeric, not a factor.

val.labels

Optional character vector, to set value label attributes of recoded variable (see vignette Labelled Data and the sjmisc-Package). If NULL (default), no value labels will be set. Value labels can also be directly defined in the rec-syntax, see 'Details'.

var.label

Optional string, to set variable label attribute for the returned variable (see vignette Labelled Data and the sjmisc-Package). If NULL (default), variable label attribute of x will be used (if present). If empty, variable label attributes will be removed.

inclusive

Logical; if TRUE, cut point value are included in the preceeding group. This may be necessary if cutting a vector into groups does not define proper ("equal sized") group sizes. See 'Note' and 'Examples'.

append

Logical, if TRUE and x is a data frame, x including the new variables as additional columns is returned; if FALSE (the default), only the new variables are returned.

suffix

String value, will be appended to variable (column) names of x, if x is a data frame. If x is not a data frame, this argument will be ignored. The default value to suffix column names in a data frame depends on the function call:

• recoded variables (rec()) will be suffixed with "_r"

• recoded variables (recode_to()) will be suffixed with "_r0"

• dichotomized variables (dicho()) will be suffixed with "_d"

• grouped variables (split_var()) will be suffixed with "_g"

• grouped variables (group_var()) will be suffixed with "_gr"

• standardized variables (std()) will be suffixed with "_z"

• centered variables (center()) will be suffixed with "_c"

Value

A grouped variable with equal sized groups. If x is a data frame, for append = TRUE, x including the grouped variables as new columns is returned; if append = FALSE, only the grouped variables will be returned.

Details

split_var() splits a variable into equal sized groups, where the amount of groups depends on the groupcount-argument. Thus, this functions cuts a variable into groups at the specified quantiles.

By contrast, group_var recodes a variable into groups, where groups have the same value range (e.g., from 1-5, 6-10, 11-15 etc.).

See Also

group_var to group variables into equal ranged groups, or rec to recode variables.

Examples

# NOT RUN {
data(efc)
# non-grouped
table(efc$neg_c_7)

# split into 3 groups
table(split_var(efc$neg_c_7, groupcount = 3))

# split multiple variables into 3 groups
split_var(efc, neg_c_7, pos_v_4, e17age, groupcount = 3)
frq(split_var(efc, neg_c_7, pos_v_4, e17age, groupcount = 3))

# original
table(efc$e42dep)

# two groups, non-inclusive cut-point
# vector split leads to unequal group sizes
table(split_var(efc$e42dep, groupcount = 2))

# two groups, inclusive cut-point
# group sizes are equal
table(split_var(efc$e42dep, groupcount = 2, inclusive = TRUE))

# }