dat.furukawa2003.RdResults on depression severity from 17 studies comparing low dosage tricyclic antidepressants (TCA) and placebo for the treatment of depression.
dat.furukawa2003The data frame contains the following columns:
| author | character | First author with information on dosage in parentheses |
| Ne | integer | number of patients in the low TCA group |
| Me | numeric | depression severity (low TCA) |
| Se | numeric | standard deviation (low TCA) |
| Nc | integer | number of patients in the placebo group |
| Mc | numeric | depression severity (placebo) |
| Sc | numeric | standard deviation (placebo) |
| measure | character | depression scale |
Furukawa et al. (2003) carried out a systematic review comparing low dosage tricyclic antidepressants (TCA) with placebo for the treatment of depression. They reported the effect on presence/absence of depression and on depression severity at various time points. Here we focus on depression severity at four weeks (Analysis 1.2.3). Most studies used some version of the Hamilton Depression Rating Scale, however, some studies used the Montgomery-Asberg Depression Rating Scale. Accordingly, it is not possible to pool the estimated effects in terms of mean differences. Instead, standardized mean differences can be used to make the effects comparable across studies using different scales.
This data set is used as an example in Schwarzer et al. (2015).
Furukawa, T. A., McGuire, H., & Barbui, C. (2003). Low dosage tricyclic antidepressants for depression. Cochrane Database of Systematic Reviews, 3, CD003197. https://doi.org/10.1002/14651858.CD003197
Schwarzer, G., Carpenter, J. R., & Rücker, G. (2015). Meta-analysis with R. Cham, Switzerland: Springer.
psychology, psychiatry, standardized mean differences
### Show first five studies
head(dat.furukawa2003, 5)
#> author Ne Me Se Nc Mc Sc measure
#> 1 Blashki(75&150) 13 6.4 5.4 18 11.4 9.6 HRSD-17
#> 2 Hormazabal(86) 17 11.0 8.2 16 19.0 8.2 HRSD-21
#> 3 Jacobson(75-100) 10 17.5 8.8 6 23.0 8.8 HRSD-24
#> 4 Jenkins(75) 7 12.3 9.9 7 20.0 10.5 BDI
#> 5 Lecrubier(100) 73 15.7 10.6 73 18.7 10.6 MADRS
### Load meta package
suppressPackageStartupMessages(library(meta))
### Use RevMan5 settings
oldset <- settings.meta("RevMan5", digits = 2)
### Conduct random effects meta-analysis with Hedges' g as effect measure
mc2 <- metacont(Ne, Me, Se, Nc, Mc, Sc, common = FALSE,
data = dat.furukawa2003, sm = "SMD")
mc2
#> Number of studies: k = 17
#> Number of observations: o = 902 (o.e = 479, o.c = 423)
#>
#> SMD 95% CI z p-value
#> Random effects model -0.59 [-0.87, -0.30] -4.04 < 0.0001
#>
#> Quantifying heterogeneity (with 95% CIs):
#> tau^2 = 0.231 [0.138, 0.981]; tau = 0.4806 [0.3710, 0.9906]
#> I^2 = 73% [55%, 83%]; H = 1.91 [1.50, 2.43]
#>
#> Test of heterogeneity:
#> Q d.f. p-value
#> 58.27 16 < 0.0001
#>
#> Details of meta-analysis methods:
#> - Inverse variance method
#> - DerSimonian-Laird estimator for tau^2
#> - Jackson method for confidence interval of tau^2 and tau
#> - Calculation of I^2 based on Q
#> - Hedges' g (bias corrected standardised mean difference)
### Use previous settings
settings.meta(oldset)