dating_wide

A data set from Field et al (2012)

datasets

A common task faced by researchers is the creation of APA style
(i.e., American Psychological Association style) tables from statistical
output. In R a large number of function calls are often needed to obtain all of
the desired information for a single APA style table. As well, the process of
manually creating APA style tables in a word processor is prone to transcription
errors. This package creates Word files (.doc files) containing APA style tables
for several types of analyses. Using this package minimizes transcription errors
and reduces the number commands needed by the user.

David Stanley

apaTables

Create American Psychological Association (APA) Style Tables

dating_wide function

A data frame with 20 rows and 11 columns. Gender is a between subjects variable. Looks and Personality are within subject variables. Both gender and particpant are factors.<dl class="dl-horizontal">
 <dt>participant</dt><dd>Factor: Participant ID number</dd>
 <dt>gender</dt><dd>Factor: Gender: Male/Female</dd>
 <dt>attractive_high</dt><dd>Date rating where looks=attractive and personality=high</dd>
 <dt>average_high</dt><dd>Date rating where looks=average and personality=high</dd>
 <dt>ugly_high</dt><dd>Date rating where looks=ugly and personality=high</dd>
 <dt>attractive_some</dt><dd>Date rating where looks=attractive and personality=some</dd>
 <dt>average_some</dt><dd>Date rating where looks=average and personality=some</dd>
 <dt>ugly_some</dt><dd>Date rating where looks=ugly and personality=some</dd>
 <dt>attractive_none</dt><dd>Date rating where looks=attractive and personality=none</dd>
 <dt>average_none</dt><dd>Date rating where looks=average and personality=none</dd>
 <dt>ugly_none</dt><dd>Date rating where looks=ugly and personality=none</dd>
</dl>

Format

dating data from textbook — dating_wide

A data frame with 20 rows and 11 columns. Gender is a between subjects variable. Looks and Personality are within subject variables. Both gender and particpant are factors.<dl class='dl-horizontal'>
 <dt>participant</dt><dd>Factor: Participant ID number</dd>
 <dt>gender</dt><dd>Factor: Gender: Male/Female</dd>
 <dt>attractive_high</dt><dd>Date rating where looks=attractive and personality=high</dd>
 <dt>average_high</dt><dd>Date rating where looks=average and personality=high</dd>
 <dt>ugly_high</dt><dd>Date rating where looks=ugly and personality=high</dd>
 <dt>attractive_some</dt><dd>Date rating where looks=attractive and personality=some</dd>
 <dt>average_some</dt><dd>Date rating where looks=average and personality=some</dd>
 <dt>ugly_some</dt><dd>Date rating where looks=ugly and personality=some</dd>
 <dt>attractive_none</dt><dd>Date rating where looks=attractive and personality=none</dd>
 <dt>average_none</dt><dd>Date rating where looks=average and personality=none</dd>
 <dt>ugly_none</dt><dd>Date rating where looks=ugly and personality=none</dd>
</dl>

dating_wide: dating data from textbook

Description

Usage

Arguments

Format

References