createCube4CATA: create a "Brick" of data and contingency table from CATA df.

In HerveAbdi/PTCA4CATA: Partial Triadic Analysis (PTCA) for Check All That Apply (CATA) Data

create a "Brick" of data and contingency table from CATA df.

Description

take a df containing CATA data and create the CATA 0/1/ Data Brick and a contingency table. The contingency table can be analyzed by correspondence analysis or Hellinger analysis. The cube of data is needed to perform correct pemutations test and to compute bootstrap confidence intervals and bootstrap ratios. With I products, J adjectives and K judges The data in the excel file are organized as: row 1 column 1 = name of Judge 1 row 1 columns (2 to J+1) name of the adjectives row 2 column 1 = name of product 1. row 2 column (2 to J+1) 0/1 answers of Judge 1 to the J adjectives for product 1 .... row I+1 column 1 = name of product I row 2 column (2 to J+1) 0/1 answers row I+2 column 1 = name of product 1. row 2 column (2 to J+1) 0/1 answers of Judge 2 to the J adjectives for product 1 .... And so on till the last judge. See df ***** as data for an example Current version uses XLConnect, and so needs JAVA and rJava A newer version is likely to use Wickham's readxl package

Usage

createCube4CATA(df, orderProducts = TRUE, threshold4cleaning = 0)

Arguments

df	a data frame with the CATA data (coded as indicated above)
orderProducts	if TRUE (default) alphabetically order the products.
threshold4cleaning	a threshold: the columns whose total is smaller than threshold4cleaning are eliminated from the data default: threshold4cleaning = 0.

Value

A list with CATA.Brick a product by adjective by judge Brick of 0/1 data (1 if judge chose adjective for product, 0 if not); ContingencyTable: A product by adjective contingency table; CleanedContingencyTable: A product by adjective cleaned contingency table (columns whose sum is equal or below threshold are dropped).

Author(s)

Herve Abdi

HerveAbdi/PTCA4CATA documentation built on July 17, 2022, 5:41 a.m.