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
describeBy(x, group=NULL,mat=FALSE,type=3,digits=15,data,...)
describe.by(x, group=NULL,mat=FALSE,type=3,...) # deprecateda data.frame or matrix. See note for statsBy.
a grouping variable or a list of grouping variables. (may be ignored if calling using the formula mode.)
provide a matrix output rather than a list
Which type of skew and kurtosis should be found
When giving matrix output, how many digits should be reported?
Needed if using formula input
parameters to be passed to describe
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
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).
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.
# 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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