aom | R Documentation |
Meta-analysis data set including 5 studies on treatment failure of short course (less than 7 days) versus long course (> 7 days) antibiotics for acute otitis media in children. The outcome considered is treatment failure at 8-19 days.
data(aom)
A data frame with 5 observations on the following 7 variables:
study
character string, label of the study
f.t
integer, number of patients for whom the short course antibiotics treatment failed
n.t
integer, number of patients receiving short course antibiotics
f.c
integer, number of patients for whom the long course antibiotics treatment failed
n.c
integer, number of patients receiving long course antibiotics
y
numeric, log odds ratio estimates for the individual studies
sigma
numeric, standard error of the log odds ratio estimate for the individual studies
This data set has been analyzed in Kozyrskyj et al. (2000) and reanalyzed by Lambert et al. (2005). Senn (2007, Section 2) discusses problems in this data set. In particular, one arm of one study has been included twice in the data set.
The counts f.t
, n.t
, f.c
and n.c
and the
names of the studies are taken from Senn (2007),
who reproduces the data set given in Kozyrskyj et al. (2000, Analysis 2.2).
The log odds ratio estimates and standard errors were computed using the escalc
function in the
package metafor
and
are identical to the estimates used in Lambert et al. (2005).
Senn, S. (2007). Trying to be precise about vagueness. Statistics in Medicine, 26, 1417–1430. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/sim.2639")}
Kozyrskyj, A., Klassen, T. P., Moffatt, M., Harvey K. (2000). Short-course antibiotics for acute otitis media. Cochrane Database of Systematic Reviews, Issue 2, Art. No.: CD001095. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/14651858.CD001095")}
Lambert, P., Sutton, A., Burton, P., Abrams, K., Jones, D. (2005). How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS. Statistics in Medicine 24(15), 2401–2428. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/sim.2112")}
data(aom)
str(aom)
# forest plot
forest(x=aom$y, sei=aom$sigma, xlab="log odds ratio")
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