removeExceptionalValues: removeExceptionalValues

In userfriendlyscience: Quantitative Analysis Made Accessible

Description

A function to replace exceptional values with NA. This can be used to quickly remove impossible values, for example, when participants entered their age as 344.

Usage

removeExceptionalValues(dat, items = NULL, exception = 0.005,
                        silent = FALSE, stringsAsFactors = FALSE)

Arguments

dat	The dataframe containing the items to inspect.
items	The items to inspect.
exception	How rare a value must be to be considered exceptional (and replaced by NA).
silent	Can be used to suppress messages.
stringsAsFactors	Whether to convert strings to factors when creating a dataframe from lapply output.

Details

Note that exceptional values may be errors (e.g. participants accidently pressed a key twice, or during data entry, something went wrong), but they may also be indicative of participants who did not seriously participate in the study. Therefore, it is advised to first use exceptionalScores to look for patterns where participants enter many exceptional scores.

Value

The dataframe, with exceptional values replaced by NA.

Author(s)

Gjalt-Jorn Peters

Maintainer: Gjalt-Jorn Peters <[e-mail]>

See Also

exceptionalScores

Examples

removeExceptionalValues(mtcars, exception=.1);

userfriendlyscience documentation built on May 2, 2019, 1:09 p.m.