reader: Who is a Regular Reader?
In catdata: Categorical Data

reader

R Documentation

Who is a Regular Reader?

Description

The reader data contains information on the reading behaviour of women refering to a specific woman's journal.

Usage

data(reader)

Format

A data frame with 48 observations on the following 5 variables. Considering the weighting variable "Freq", there are 941 observations.

RegularReader: Is the woman a regular reader? yes = 1, no = 0
Working: Is the woman working? yes = 1, no = 0
Age: Age of the woman in categories (18–29 years = 1, 30–39 = 2, 40–49 = 3)
Education: Level of education. L1 = 11, L2 = 12, L3 = 13, L4 = 14
Freq: Frequency of the observation

Source

Fahrmeir, Hamerle and Tutz (1996), Multivariate statistische Verfahren, Berlin: de Gruyter

catdata documentation built on June 22, 2024, 12:28 p.m.

catdata index

Package overview Addiction - Additive Multinomial Logit Models Addiction - Multinomial Model Addiction - Multinomial Model with Hierarchically Structured Response AIDS - Semiparametric Mixed Model Arthritis - Cumulative Logit Model Beta-blockers - Discrete Mixture Models Birth Data - Bivariate Binary GEE Birth Data - Bivariate Binary Regression Birth Data - Loglinear Models Duration of Unemployment - Analysis of Deviance Table for Nested Models Duration of Unemployment - Cubic B-Splines Duration of Unemployment - Different Codings of Covariables Duration of Unemployment - Logit Model Duration of Unemployment - Trees Encephalitis - Loglinear Poisson Model and Normal Distribution Model Exposure to Dust - Generalized Additive Models Exposure to Dust - Logistic Regression and Search for Outliers Exposure to Dust - Trees Foodstamp - Residuals of Logistic Regression Insolvency - (Quasi-)Poisson Model and Negative Binomial Model Knee Data - Discrete Mixture Model Knee Data - Random Effects Logit Models Knee Data - Sequential/Cumulative Random Effects Logit Models Knee Injuries - Comparison of Link Functions Knee Injuries - Marginal Models Knee Injuries - Proportional Odds Models Leukoplakia - Mosaic Plots Medical Care - Comparison of different count data models Medical Care - Zero-Inflated and Zero-Hurdle-Model Number of Children - Partially Additive Model Number of Children - Poisson Models with Polynomial Terms Party Preference - Star Plots Preference for Political Parties - Multinomial Logit Model Retinopathy - Sequential Logit Models Retinopathy - Testing Proportional Odds Assumption Teratology - Alternative Binary Models Travel Mode - Multinomial Logit Model Vaso Constriction - Logistic Regression

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