caesarean: Caesarean Birth Data

In binomlogit: Efficient MCMC for Binomial Logit Models

Description

The data set contains information on infection from births by Caesarean section, originating from a 3-way contingency table. 251 mothers were categorized by the variables "Caesarean planned" (yes/no), "antibiotics given" (yes/no) and "risk factors present" (yes/no). To obtain data for a binary regression model the originally observed two types of infection are ignored and just the binary event "infection" or "no infection" is considered. For the binomial logit regression model all binary observations with the same covariate pattern are aggregated to a binomial observation.

Usage

data(caesarean)

data(caesarean_aux)

data(caesarean_binary)

Format

The binomial data set caesarean consists of 8 binomial observations (= aggregated binary observations) and the following 6 variables:

yi

number of women with infection

Ni

number of observed women in each group

intercept

column consisting of ones

planned

Caesarean birth planned (1 = yes, 0 = no)

riskfactors

risk factors present (1 = yes, 0 = no)

antibiotics

antibiotics given (1 = yes, 0 = no)

The binary data set caesarean_binary consists of 251 binary observations and the following 5 variables:

y

infection (1 = yes, 0 = no)

planned

Caesarean birth planned (1 = yes, 0 = no)

riskfactors

risk factors present (1 = yes, 0 = no)

antibiotics

antibiotics given (1 = yes, 0 = no)

intercept

column consisting of ones

To run auxiliary mixture sampling in the individual dRUM representation of the binomial logit model the binary data set should have the same form as the binomial data set. For this purpose a column consisting of ones is added to the binary data set. The data set caesarean_aux then consists of 251 observations and the following 6 variables:

yi

number of women with infection

Ni

number of observed women in each group, which is equal to 1 for all observations

planned

Caesarean birth planned (1 = yes, 0 = no)

riskfactors

risk factors present (1 = yes, 0 = no)

antibiotics

antibiotics given (1 = yes, 0 = no)

intercept

column consisting of ones

Source

Fahrmeir, L. and Tutz, G. (2001) Multivariate Statistical Modelling based on Generalized Linear Models, 2nd Ed. Springer Series in Statistics. Springer, New York/Berlin/Heidelberg.

See Also

dRUMIndMH, dRUMAuxMix, dRUMHAM, IndivdRUMIndMH

Examples

  data(caesarean)
  data(caesarean_binary)
  data(caesarean_aux)
  ## see dRUMIndMH, dRUMAuxMix, dRUMHAM and IndivdRUMIndMH documentation
  ## for examples using these data

Example output

binomlogit documentation built on May 1, 2019, 7:28 p.m.