means_by_group {datawizard} | R Documentation |
Summary of mean values by group
Description
Computes summary table of means by groups.
Usage
means_by_group(x, ...)
## S3 method for class 'numeric'
means_by_group(
x,
by = NULL,
ci = 0.95,
weights = NULL,
digits = NULL,
group = NULL,
...
)
## S3 method for class 'data.frame'
means_by_group(
x,
select = NULL,
by = NULL,
ci = 0.95,
weights = NULL,
digits = NULL,
exclude = NULL,
ignore_case = FALSE,
regex = FALSE,
verbose = TRUE,
group = NULL,
...
)
Arguments
x |
A vector or a data frame.
|
... |
Currently not used
|
by |
If x is a numeric vector, by should be a factor that
indicates the group-classifying categories. If x is a data frame, by
should be a character string, naming the variable in x that is used for
grouping. Numeric vectors are coerced to factors. Not that by should
only refer to a single variable.
|
ci |
Level of confidence interval for mean estimates. Default is 0.95 .
Use ci = NA to suppress confidence intervals.
|
weights |
If x is a numeric vector, weights should be a vector of
weights that will be applied to weight all observations. If x is a data
frame, weights can also be a character string indicating the name of the
variable in x that should be used for weighting. Default is NULL , so no
weights are used.
|
digits |
Optional scalar, indicating the amount of digits after decimal
point when rounding estimates and values.
|
group |
Deprecated. Use by instead.
|
select |
Variables that will be included when performing the required
tasks. Can be either
a variable specified as a literal variable name (e.g., column_name ),
a string with the variable name (e.g., "column_name" ), or a character
vector of variable names (e.g., c("col1", "col2", "col3") ),
a formula with variable names (e.g., ~column_1 + column_2 ),
a vector of positive integers, giving the positions counting from the left
(e.g. 1 or c(1, 3, 5) ),
a vector of negative integers, giving the positions counting from the
right (e.g., -1 or -1:-3 ),
one of the following select-helpers: starts_with() , ends_with() ,
contains() , a range using : or regex("") . starts_with() ,
ends_with() , and contains() accept several patterns, e.g
starts_with("Sep", "Petal") .
or a function testing for logical conditions, e.g. is.numeric() (or
is.numeric ), or any user-defined function that selects the variables
for which the function returns TRUE (like: foo <- function(x) mean(x) > 3 ),
ranges specified via literal variable names, select-helpers (except
regex() ) and (user-defined) functions can be negated, i.e. return
non-matching elements, when prefixed with a - , e.g. -ends_with("") ,
-is.numeric or -(Sepal.Width:Petal.Length) . Note: Negation means
that matches are excluded, and thus, the exclude argument can be
used alternatively. For instance, select=-ends_with("Length") (with
- ) is equivalent to exclude=ends_with("Length") (no - ). In case
negation should not work as expected, use the exclude argument instead.
If NULL , selects all columns. Patterns that found no matches are silently
ignored, e.g. extract_column_names(iris, select = c("Species", "Test"))
will just return "Species" .
|
exclude |
See select , however, column names matched by the pattern
from exclude will be excluded instead of selected. If NULL (the default),
excludes no columns.
|
ignore_case |
Logical, if TRUE and when one of the select-helpers or
a regular expression is used in select , ignores lower/upper case in the
search pattern when matching against variable names.
|
regex |
Logical, if TRUE , the search pattern from select will be
treated as regular expression. When regex = TRUE , select must be a
character string (or a variable containing a character string) and is not
allowed to be one of the supported select-helpers or a character vector
of length > 1. regex = TRUE is comparable to using one of the two
select-helpers, select = contains("") or select = regex("") , however,
since the select-helpers may not work when called from inside other
functions (see 'Details'), this argument may be used as workaround.
|
verbose |
Toggle warnings.
|
Details
This function is comparable to aggregate(x, by, mean)
, but provides
some further information, including summary statistics from a One-Way-ANOVA
using x
as dependent and by
as independent variable. emmeans::contrast()
is used to get p-values for each sub-group. P-values indicate whether each
group-mean is significantly different from the total mean.
Value
A data frame with information on mean and further summary statistics
for each sub-group.
Examples
data(efc)
means_by_group(efc, "c12hour", "e42dep")
data(iris)
means_by_group(iris, "Sepal.Width", "Species")
# weighting
efc$weight <- abs(rnorm(n = nrow(efc), mean = 1, sd = .5))
means_by_group(efc, "c12hour", "e42dep", weights = "weight")
[Package
datawizard version 0.12.2
Index]