smoking {meta}

Smoking example

Description

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

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

Details

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 (dataset smoking) and lung-cancer deaths (dataset lungcancer), respectively.

The person time is attributed such that the rate ratios are equal to the reported mortality ratios implicitly 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.

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.

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)