chds: Christchurch Health and Development Study

In bnmonitor: An Implementation of Sensitivity Analysis in Bayesian Networks

Christchurch Health and Development Study

Description

Simulated data and Bayesian networks from the Christchurch Health and Development Study

Usage

chds

chds_bn

chds_bn.fit

Format

The dataframe chds includes 500 observations randomly simulated from the bn.fit object chds_bn.fit. It has four variables:

• Social: family's social background with levels "High" and "Low"

• Economic: family's economic status with levels "High" and "Low"

• Events: number of family life events with levels "High", "Average" and "Low"

• Admission: hospital admission of the child with levels "yes" and "no"

• statistics: mark out of 100 for statistics

chds_bn is an object of class bn including the MAP Bayesian network from Barclay et al. (2013) and chds_bn.fit is an object of class bn.fit including the probabilities from the same article.

An object of class data.frame with 500 rows and 4 columns.

An object of class bn of length 3.

An object of class bn.fit (inherits from bn.fit.dnet) of length 4.

References

Fergusson, D. M., Horwood, L. J., & Shannon, F. T. (1986). Social and family factors in childhood hospital admission. Journal of Epidemiology & Community Health, 40(1), 50-58.

Barclay, L. M., Hutton, J. L., & Smith, J. Q. (2013). Refining a Bayesian network using a chain event graph. International Journal of Approximate Reasoning, 54(9), 1300-1309.

bnmonitor documentation built on June 7, 2023, 5:19 p.m.