WordPools (version 1.2.0)

CatProp: Joelson-Hermann Category Properties

Description

Properties of the 56 taxonomic categories from the Battig-Montague category norms published by Joelson and Hermann (1978).

Usage

data(CatProp)

Format

A data frame with 56 observations on the following 24 variables.

catnum

Category number, a numeric variable

catname

Category name, a character variable

rnatrl

Rated naturalness 1..7, a numeric variable

rfamil

Rated familiarity 1..7, a numeric variable

rmeang

Rated meaningfulness 1..7 (Hunt & Hodge, 1971), a numeric variable

rfreq

Rated frequency 1..7 B&M, a numeric variable

genfreq

Generated category label frequency, a numeric variable

rageoaq

Rated age of acquisition 1..10, a numeric variable

rsize

Estimated category size, a numeric variable

ts_30

Mean # types produced in 30 seconds, a numeric variable

rclasm

Recall asymptote, a numeric variable

rclrate

Recall rate parameter, a numeric variable

tas

Types across subjects, a numeric variable

cortas

Corrected types across subjects, a numeric variable

ntf

# of types produced first, a numeric variable

nmngox

# of dictionary meanings (Oxford), a numeric variable

nmngam

# of dictionary meanings (Am. Heritage), a numeric variable

catfreqp

category label K-F frequency, a numeric variable

rabcon

Rated abstract-concreteness 1..7, a numeric variable

rvagprc

Rated vague-precise 1..7, a numeric variable

exfreqp

Avg exemplar log K-F frequency, a numeric variable

intsam

Intersample correlation, a numeric variable

maxfreq

Maximum response frequency, a numeric variable

pagmt

Percent agreement on category membership, a numeric variable

Details

Includes data for all 56 of the Battig-Montague categories from a preprint of the Joelson-Hermann paper Values for catfreqp were added for categories 3, 4, 8, 15, 24, 27, 32, 46, 47 & 56 from the Kucera-Francis norms, ignoring "part of", "unit of", and taking max of labels connected by "or".

Examples

data(CatProp)
summary(CatProp)
plot(CatProp[,3:10])

# try a biplot
CP <- CatProp
rownames(CP) <- CP$catname
biplot(prcomp(na.omit(CP[,3:12]), scale=TRUE))

# select some categories where the rated age of acquisition is between 2-4
cats <- pickList(CatProp, list(rageoaq=c(2,4)))
cats[,2:9]

# pick some fruit
pickList(subset(Battig, catname=="fruit"))