Converting means and standard deviations
convert_mean.Rd
Converting estimated means and standard deviations in experimental and contorol groups to the effect size estimates and the within studies standard errors vector
Arguments
- n1
A vector of number of observations in experimental group
- m1
A vector of estimated mean in experimental group
- s1
A vector of standard deviation in experimental group
- n2
A vector of number of observations in experimental group
- m2
A vector of estimated mean in experimental group
- s2
A vector of standard deviation in experimental group
- pooled
logical; if
TRUE
, a pooled variance is used. The default isFALSE
.
Value
A data.frame
of study data.
y
: A numeric vector of the effect size estimates.se
: A numeric vector of the within studies standard error estimates.
Examples
require("flexmeta")
#> Loading required package: flexmeta
#> Warning: there is no package called 'flexmeta'
data("clbp")
dat <- convert_mean(clbp$n1, clbp$m1, clbp$s1, clbp$n2, clbp$m2, clbp$s2)
print(dat)
#> y se
#> 1 2.00 3.144921
#> 2 3.00 3.262923
#> 3 -2.00 4.132601
#> 4 3.30 3.745650
#> 5 5.00 3.745650
#> 6 8.30 5.884007
#> 7 1.00 8.179348
#> 8 -6.00 2.805140
#> 9 3.50 4.104256
#> 10 0.50 4.081157
#> 11 -5.84 5.313543
#> 12 -3.98 5.279749
#> 13 4.50 3.489772
#> 14 -2.00 2.066928
#> 15 -4.00 2.073189
#> 16 -37.60 2.829912
#> 17 4.00 7.205716
#> 18 -19.40 1.593289
#> 19 -8.00 2.120946
#> 20 0.06 1.891965
#> 21 -0.20 2.664159
#> 22 10.80 7.260702
#> 23 -27.20 8.747905