center

<code>center</code> centers and/or standardized a numeric vector. It is an
alternative to <code>scale.default</code> that returns a numeric vector rather than
a numeric matrix.

Offers a suite of functions to prepare questionnaire data for analysis (perhaps other types of data as well). By data preparation, I mean data analytic tasks to get your raw data ready for statistical modeling (e.g., regression). There are functions to investigate missing data, reshape data, validate responses, recode variables, score questionnaires, center variables, aggregate by groups, shift scores (i.e., leads or lags), etc. It provides functions for both single level and multilevel (i.e., grouped) data. With a few exceptions (e.g., ncases()), functions without an "s" at the end of their primary word (e.g., center_by()) act on atomic vectors, while functions with an "s" at the end of their primary word (e.g., centers_by()) act on multiple columns of a data.frame.

David Disabato

quest

Prepare Questionnaire Data for Analysis

center function

<dl><dt>x</dt>
<dd>numeric vector.</dd>
<dt>center</dt>
<dd>logical vector with length 1 specifying whether grand-mean
centering should be done.</dd>
<dt>scale</dt>
<dd>logical vector with length 1 specifying whether grand-SD scaling
should be done.</dd></dl>

Arguments

Centering and/or Standardizing a Numeric Vector — center

<dl>

<dt>x</dt>
<dd>numeric vector.</dd>


<dt>center</dt>
<dd>logical vector with length 1 specifying whether grand-mean
centering should be done.</dd>


<dt>scale</dt>
<dd>logical vector with length 1 specifying whether grand-SD scaling
should be done.</dd>

</dl>

center: Centering and/or Standardizing a Numeric Vector

Description

Usage

Value

Arguments

Details

See Also

Examples