carcinoma: Diagnoses of carcinoma (sample data)

In dlinzer/poLCA: Polytomous Variable Latent Class Analysis

Diagnoses of carcinoma (sample data)

Description

Dichotomous ratings by seven pathologists of 118 slides for the presence or absence of carcinoma in the uterine cervix. Pathologists are labeled A through G. There were 20 different observed response patterns. This data set appears in Agresti (2002, p. 542) as Table 13.1.

Usage

data(carcinoma)

Format

A data frame with 118 observations on 7 variables representing pathologist ratings with 1 denoting "no" and 2 denoting "yes".

Source

Agresti, Alan. 2002. Categorical Data Analysis, second edition. Hoboken: John Wiley \& Sons.

Examples

##
## Replication of latent class models in Agresti (2002, p. 543), 
## Table 13.2 and Table 13.3.
##
data(carcinoma)
f <- cbind(A,B,C,D,E,F,G)~1
lca2 <- poLCA(f,carcinoma,nclass=2) # log-likelihood: -317.2568
lca3 <- poLCA(f,carcinoma,nclass=3) # log-likelihood: -293.705
lca4 <- poLCA(f,carcinoma,nclass=4,nrep=10,maxiter=5000) # log-likelihood: -289.2858 

dlinzer/poLCA documentation built on April 7, 2022, 10:19 p.m.