Learn R Programming

metaplus (version 1.0-5)

exercise: Exercise meta-analysis data

Description

Lawlor & Hopker (2001) performed a meta-analysis of trials of exercise in the management of depression, which was subsequently analysed using meta- regression (Higgins & Thompson 2004) with duration of treatment as a covariate. There is a possible outlier, the study by Reuter. While there are additional predictors, it seems excessive to use them given the small number of studies.

Usage

exercise

Arguments

Format

A data frame with 10 observations on the following 9 variables.

study

study author

smd

study effect estimate

varsmd

study effect variance

sesmd

study effect standard error

abstract

study available as abstract only?

duration

length of study in weeks

itt

intention to treat analysis?

alloc

outcome assessor blinded

phd

phd thesis?

References

Higgins, J. P. T., & Thompson, S. G. (2004). Controlling the risk of spurious findings from meta-regression. Statistics in Medicine, 23(11), 166382. doi:10.1002/sim.1752

Lawlor, D. A., & Hopker, S. W. (2001). The effectiveness of exercise as an intervention in the management of depression: systematic review and meta-regression analysis of randomised controlled trials. BMJ, 322(31 March), 18.

Examples

Run this code
# \donttest{
exercise1 <- metaplus(smd, sqrt(varsmd), mods = duration, slab = study,
    cores = 1, data = exercise)
exercise2 <- metaplus(smd, sqrt(varsmd), mods = cbind(duration, itt), slab = study,
    cores = 1, data = exercise)
# }

Run the code above in your browser using DataLab