Description Usage Arguments Details Value References Examples
Computes the reference standard deviation of the
given meta-analysis data set.
Depending on the argument type_sigma_ref
, either
a geometric or weighted harmonic mean is used.
1 |
df |
data frame with one column "sigma" containing the standard errors of the estimates for the individual studies |
type_sigma_ref |
either |
If type_sigma_ref="geometric"
, the reference standard deviation is given by the geometric mean
of the standard deviations of the individual studies
(Sorbye & Rue 2014 (equation (7)).
If type_sigma_ref="harmonic"
, the reference standard deviation σ_{ref} is
the square root of a weighted harmonic mean of the variances of the individual studies,
as described in Hoaglin (2016, page 490).
More precisely, we have
σ_{ref} = √{ (k-1) ∑ w_i /((∑ w_i)^2 - ∑ w_i^2)},
where k is the number of studies in the data frame df
and the weights are
w_i=σ_i^{-2}, i =1, ... , k, for the standard deviations σ_i (or standard errors)
of the individual studies.
The reference standard deviation of the data set. Non-negative real number.
Sorbye, S., Rue, H. (2014). Scaling intrinsic Gaussian Markov random field priors in spatial modelling. Spatial Statistics 8, 39–51. https://doi.org/10.1016/j.spasta.2013.06.004
Hoaglin, D. (2016). Misunderstandings about Q and "Cochran's Q test" in meta-analysis. Statistics in Medicine 35(4), 485–495. https://doi.org/10.1002/sim.6632
1 2 3 4 5 6 7 8 | # Acute Graft rejection data analyzed in Friede et al. (2017), Sect. 3.2,
# URL: https://doi.org/10.1002/bimj.201500236
df <- data.frame(y = c(-2.310, -1.258), # log-odds-ratio
sigma = c(0.599, 0.642), # SE(log-odds-ratio)
labels = c(1:2))
sigma_ref(df=df)
sigma_ref(df=df, type_sigma_ref="harmonic")
|
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