Smoking example

Description

Meta-analyses on the effect of smoking on mortality risk.

Data have been reconstructed based on the famous Smoking and Health Report to the Surgeon General (Bayne-Jones S et al., 1964). Data sets can be used to evaluate the risk of smoking on overall mortality and lung-cancer deaths, respectively. The person time is attributed such that the rate ratios are equal to the reported mortality ratios implicitely assuming that the data have arisen from a homogeneous age group; more detailed information by age is not available from the report. Note, the group of "non-smokers" actually consists of all participants except those who are smokers of cigarettes only. Information on real non-smokers is not available from the published Smoking and Health Report.

Usage

data(smoking)

data(lungcancer)

Format

A data frame with the following columns:

study

Study label

participants

Total number of participants

d.smokers

Number of deaths in smokers' group

py.smokers

Person years at risk in smokers' group

d.nonsmokers

Number of deaths in non-smokers' group

py.nonsmokers

Person years at risk in non-smokers' group

Source

Bayne-Jones S et al. (1964), Smoking and Health: Report of the Advisory Committee to the Surgeon General of the United States. U-23 Department of Health, Education, and Welfare. Public Health Service Publication No. 1103. http://profiles.nlm.nih.gov/ps/retrieve/ResourceMetadata/NNBBMQ

See Also

metainc

Examples

data(smoking)

m1 <- metainc(d.smokers, py.smokers,
              d.nonsmokers, py.nonsmokers,
              data=smoking, studlab=study)
print(m1, digits=2)

data(lungcancer)

m2 <- metainc(d.smokers, py.smokers,
              d.nonsmokers, py.nonsmokers,
              data=lungcancer, studlab=study)
print(m2, digits=2)

Results