psych (version 1.1.11)

describe: Basic descriptive statistics useful for psychometrics

Description

There are many summary statistics available in R; this function provides the ones most useful for scale construction and item analysis in classic psychometrics. Range is most useful for the first pass in a data set, to check for coding errors.

Usage

describe(x, na.rm = TRUE, interp=FALSE,skew = TRUE, ranges = TRUE,trim=.1)

Arguments

x
A data frame or matrix
na.rm
The default is to delete missing data. na.rm=FALSE will delete the case.
interp
Should the median be standard or interpolated
skew
Should the skew and kurtosis be calculated?
ranges
Should the range be calculated?
trim
trim=.1 -- trim means by dropping the top and bottom trim fraction

Value

  • A data.frame of the relevant statistics: item name item number number of valid cases mean standard deviation trimmed mean (with trim defaulting to .1) median (standard or interpolated mad: median absolute deviation (from the median) minimum maximum skew kurtosis standard error

Details

In basic data analysis it is vital to get basic descriptive statistics. Procedures such as summary and hmisc::describe do so. The describe function in the psych package is meant to produce the most frequently requested stats in psychometric and psychology studies, and to produce them in an easy to read data.frame. The results from describe can be used in graphics functions (e.g., error.crosses).

The range statistics (min, max, range) are most useful for data checking to detect coding errors, and should be found in early analyses of the data.

Although describe will work on data frames as well as matrices, it is important to realize that for data frames, descriptive statistics will be reported only for those variables where this makes sense (i.e., not for alphanumeric data). Variables that are categorical or logical are converted to numeric and then described. These variables are marked with an * in the row name.

In a typical study, one might read the data in from the clipboard (read.clipboard), show the splom plot of the correlations (pairs.panels), and then describe the data.

na.rm=FALSE is equivalent to describe(na.omit(x))

See Also

describe.by, skew, kurtosi interp.median, pairs.panels, read.clipboard, error.crosses

Examples

Run this code
data(sat.act)
describe(sat.act)

describe(sat.act,skew=FALSE)

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