psych (version 2.1.9)

describeBy: Basic summary statistics by group

Description

Report basic summary statistics by a grouping variable. Useful if the grouping variable is some experimental variable and data are to be aggregated for plotting. Partly a wrapper for by and describe

Usage

describeBy(x, group=NULL,mat=FALSE,type=3,digits=15,data,...)
describe.by(x, group=NULL,mat=FALSE,type=3,...)  # deprecated

Arguments

x

a data.frame or matrix. See note for statsBy.

group

a grouping variable or a list of grouping variables. (may be ignored if calling using the formula mode.)

mat

provide a matrix output rather than a list

type

Which type of skew and kurtosis should be found

digits

When giving matrix output, how many digits should be reported?

data

Needed if using formula input

...

parameters to be passed to describe

Value

A data.frame of the relevant statistics broken down by group: item name item number number of valid cases mean standard deviation median mad: median absolute deviation (from the median) minimum maximum skew standard error

Details

To get descriptive statistics for several different grouping variables, make sure that group is a list. In the case of matrix output with multiple grouping variables, the grouping variable values are added to the output.

As of July, 2020, the grouping variable(s) may be specified in formula mode (see the examples).

The type parameter specifies which version of skew and kurtosis should be found. See describe for more details.

An alternative function (statsBy) returns a list of means, n, and standard deviations for each group. This is particularly useful if finding weighted correlations of group means using cor.wt. More importantly, it does a proper within and between group decomposition of the correlation.

cohen.d will work for two groups. It converts the data into mean differences and pools the within group standard deviations. Returns cohen.d statistic as well as the multivariate generalization (Mahalanobis D).

See Also

describe, statsBy, densityBy and violinBy, cohen.d, cohen.d.by, and cohen.d.ci as well as error.bars and error.bars.by for other graphical displays.

Examples

Run this code
# NOT RUN {
data(sat.act)
describeBy(sat.act,sat.act$gender) #just one grouping variable
describeBy(sat.act ~ gender)   #describe the entire set	formula input
describeBy(SATV + SATQ ~ gender,data =sat.act)  #specify the data set if using formula
#describeBy(sat.act,list(sat.act$gender,sat.act$education))  #two grouping variables
describeBy(sat.act ~ gender +  education) #two grouping variables
des.mat <- describeBy(age ~ education,mat=TRUE,data = sat.act) #matrix (data.frame) output 
des.mat <- describeBy(age ~ education + gender, data=sat.act,
               mat=TRUE,digits=2)  #matrix output  rounded to 2 decimals            
             


# }

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