xpssDescriptives: Simple descriptive statistics
In translateSPSS2R: Toolset for Translating SPSS-Syntax to R-Code

Description Usage Arguments Details Value Author(s) Examples

R Implementation of the SPSS Function Descriptives

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xpssDescriptives(x, variables, missing = "variable", statistics = c("mean",
  "max", "min", "stddev"), save = FALSE, ztrans = list(varname = NULL, zname
  = NULL))

`x`	a (non-empty) data.frame or input data of class `"xpssFrame"`.
`variables`	atomic character or character vector with the name of the variables.
`missing`	atomic character which specifiy the missing method. The method indicates what should happen when the data contains NAs. Default is `"variable"`.
`statistics`	atomic chracter or character vector which determine the descriptiv statistics. Default are `"mean"`, `"max"`, `"min"`, `"stddev"`.
`save`	logical indicator. TRUE adds the z-score of each variable to `x`. Default is FALSE.
`ztrans`	list which specifies variables for z-transformation and name of z-transformed variables. Read Details for further information.

The xpssDescriptives function provides a set of descriptive statistic tools.

missing:

	`variable`	removes user-, and system-missing data explicitly for every variable.
	`listwise`	performs a listwise-deletion.
	`include`	includes all user-defined missing values.

statistics:

	`kurtosis`	calculates the bulge of the variable.
	`max`	displays the maximum of the variable.
	`mean`	calculates the arithmetic mean, respectively the midpoint of the variable.
	`min`	displays the minimum of the variable.
	`kurtosis`	calculates the bulge of the variable.
	`range`	displays the span between the minimum and the maximum value.
	`sekurtosis`	calculates the standrard error of the bulge of the variable.
	`semean`	displays the standard error of the arithmetic mean.
	`seskewness`	calculates the standrard error of the inclination of the variable.
	`skewness`	calculates the inclination of the variable.
	`stddev`	displays the standard deviation of the variable.
	`sum`	calculates the sum of each observation within the variable.
	`variance`	displays the variance.

ztrans input, is a list with elements varname and zname. varname and zname are either atomic characters or character vectors.
It is necessary that either both parameters are filled or blank.

Output is a list object with descriptive statistic parameters. The specific outcomes of the selected variables are stored in a list object. Every variable is stored in a different list element.

If the parameter save is TRUE, a matrix with z-transformed values will be appended at the end of the list. If ztrans is blank, the name of the matrix will be Z*varname*. Otherwise whether ztrans is not empty the user specified description in zname will be the name of the z-transformed matrix of the variable varname.

Bastian Wiessner

data(fromXPSS)

## Analyzing Variable V5, Output contains default statistics
xpssDescriptives(x=fromXPSS,
                 variables="V5")

## Analyzing Variable V7_1, Output contains default statistics
## and z-score of Variable V7_1
xpssDescriptives(x=fromXPSS,
                 variables="V7_1",
                 save = TRUE)

## Analyzing Variable V7_2, Output contains default statistics
## and z-score of Variable V7_2 store in myZname
xpssDescriptives(x=fromXPSS,
                 variables="V7_2",
                 save = TRUE,
                 ztrans = list(varname = "V7_2",
                               zname = "myZname"))

 ## Analyzing Variable V7_2, Output contains kurtosis, skewness, semean and mean
 ## missing values are included
 ## z-score get calculated and store in myZname

  xpssDescriptives(x=fromXPSS,
                 variables="V7_2",
                 statistics=c("kurtosis",
                               "skewness",
                               "semean",
                               "mean"),
                 missing="include",
                 save = TRUE,
                 ztrans = list(varname = "V7_2",
                               zname = "myZname"))