dat.hartmannboyce2018: Studies on the Effectiveness of Nicotine Replacement Therapy...

dat.hartmannboyce2018R Documentation

Studies on the Effectiveness of Nicotine Replacement Therapy for Smoking Cessation

Description

Results from 133 studies examining the effectiveness of nicotine replacement therapy (NRT) for smoking cessation at 6+ months of follow-up.

Usage

dat.hartmannboyce2018

Format

The data frame contains the following columns:

study numeric study identifier
x.nrt numeric number of participants in the NRT group who were abstinent at the follow-up
n.nrt numeric number of participants in the NRT group
x.ctrl numeric number of participants in the control group who were abstinent at the follow-up
n.ctrl numeric number of participants in the control group
treatment character type of NRT provided in the treatment group

Details

The dataset includes the results from 133 studies examining the effectiveness of nicotine replacement therapy (NRT) for smoking cessation. The results given in this dataset pertain to abstinence at 6+ months of follow-up. NRT was provided to participants in the treatment groups in various forms as indicated by the treatment variable (e.g., gum, patch, inhalator). Note that the dataset includes 136 rows, since a few studies included multiple treatments.

Concepts

medicine, smoking, risk ratios, Mantel-Haenszel method

Author(s)

Wolfgang Viechtbauer, wvb@metafor-project.org, https://www.metafor-project.org

Source

Hartmann‐Boyce, J., Chepkin, S. C., Ye, W., Bullen, C. & Lancaster, T. (2018). Nicotine replacement therapy versus control for smoking cessation. Cochrane Database of Systematic Reviews, 5, CD000146. https://doi.org//10.1002/14651858.CD000146.pub5

Examples

### copy data into 'dat' and examine data
dat <- dat.hartmannboyce2018
head(dat, 10)

## Not run: 

### load metafor package
library(metafor)

### turn treatment into a factor with the desired ordering
dat$treatment <- factor(dat$treatment, levels=unique(dat$treatment))

### meta-analysis per treatment using the M-H method
lapply(split(dat, dat$treatment), function(x)
       rma.mh(measure="RR", ai=x.nrt,  n1i=n.nrt,
                            ci=x.ctrl, n2i=n.ctrl, data=x, digits=2))

### all combined
rma.mh(measure="RR", ai=x.nrt,  n1i=n.nrt,
                     ci=x.ctrl, n2i=n.ctrl, data=dat, digits=2)


## End(Not run)

metadat documentation built on April 6, 2022, 5:08 p.m.