I'm preparing some teaching material on meta-analysis. I have some neat examples from Cochrane reviews. I run the data in Stata, with DerSimonian-Laird random effects, which is supposedly the same method (says Cochrane handbook) but get slightly different weights, effect sizes, and CIs. I remember this from a few years back too. The differences are just on the cusp of being too big to be rounding error, but then the data I am using were rounded to 1 dp in the Cochrane publication and I know from personal experience that under the hood, their RevMan software works with whatever precision you give it and always displays a disappointing 1 or 2dp.
I guess I'm just looking for reassurance that others who have encountered this believe the formulas in Stata and RevMan are the same, and the difference we see can just be brushed aside as accumulated rounding error.
=========================
here's some output and a Cochrane screen grab is attached:
. meta summarize, subgroup(japan)
Effect-size label: Weight loss (kg)
Effect size: _meta_es
Std. Err.: _meta_se
Study label: study
Subgroup meta-analysis summary Number of studies = 12
Random-effects model
Method: DerSimonian-Laird
Group: japan
Effect Size: Weight loss (kg)
--------------------------------------------------------------------
Study | Effect Size [95% Conf. Interval] % Weight
------------------+-------------------------------------------------
Group: 0 |
Auvichayapat 2008 | -1.100 -1.986 -0.214 5.22
Hill 2007 | -0.200 -0.425 0.025 9.22
Hsu 2008 | -0.100 -1.035 0.835 4.96
Diepvens2005 | 0.000 -0.377 0.377 8.42
|
theta | -0.217 -0.524 0.091
------------------+-------------------------------------------------
Group: 1 |
Kozuma 2005 | -1.300 -1.432 -1.168 9.55
Takase 2008 | -1.200 -1.371 -1.029 9.43
Nagao 2007 | -0.600 -0.752 -0.448 9.50
Takeshita 2008 | -0.400 -0.597 -0.203 9.34
Kajimoto 2005 | -0.400 -0.583 -0.217 9.39
Suzuki 2009 | -0.200 -0.553 0.153 8.56
Kataoka 2004 | -0.100 -0.363 0.163 9.05
Takashima 2004 | 0.000 -0.540 0.540 7.37
|
theta | -0.549 -0.892 -0.205
------------------+-------------------------------------------------
Overall |
theta | -0.476 -0.774 -0.179
--------------------------------------------------------------------
Heterogeneity summary
-----------------------------------------------------------------------------
Group | df Q P > Q tau2 % I2 H2
---------------+-------------------------------------------------------------
0 | 3 5.07 0.167 0.038 40.85 1.69
1 | 7 163.14 0.000 0.228 95.71 23.31
---------------+-------------------------------------------------------------
Overall | 11 202.10 0.000 0.236 94.56 18.37
-----------------------------------------------------------------------------
Test of group differences: Q_b = chi2(1) = 1.99 Prob > Q_b = 0.159
.
end of do-file

=========================
If you want to try it:
// get the data
import delimited "http://www.robertgrantstats.co.uk/data/cochrane_green_tea_weight_loss.csv", varnames(1) delimiter(",") clear
// calculate the effect size (mean difference, in this case)
meta esize n_tea mean_tea sd_tea n_control mean_control sd_control, ///
esize(mdiff) random(hschmidt) ///
studylabel(study) eslabel("Weight loss (kg)")
// get the MA results
meta summarize, subgroup(japan)
// compare with Analysis 1,4, page 61 in https://www.cochranelibrary.com/cdsr...pub2/epdf/full
sending good wishes to y'all from Hampshire UK
Robert
I guess I'm just looking for reassurance that others who have encountered this believe the formulas in Stata and RevMan are the same, and the difference we see can just be brushed aside as accumulated rounding error.
=========================
here's some output and a Cochrane screen grab is attached:
. meta summarize, subgroup(japan)
Effect-size label: Weight loss (kg)
Effect size: _meta_es
Std. Err.: _meta_se
Study label: study
Subgroup meta-analysis summary Number of studies = 12
Random-effects model
Method: DerSimonian-Laird
Group: japan
Effect Size: Weight loss (kg)
--------------------------------------------------------------------
Study | Effect Size [95% Conf. Interval] % Weight
------------------+-------------------------------------------------
Group: 0 |
Auvichayapat 2008 | -1.100 -1.986 -0.214 5.22
Hill 2007 | -0.200 -0.425 0.025 9.22
Hsu 2008 | -0.100 -1.035 0.835 4.96
Diepvens2005 | 0.000 -0.377 0.377 8.42
|
theta | -0.217 -0.524 0.091
------------------+-------------------------------------------------
Group: 1 |
Kozuma 2005 | -1.300 -1.432 -1.168 9.55
Takase 2008 | -1.200 -1.371 -1.029 9.43
Nagao 2007 | -0.600 -0.752 -0.448 9.50
Takeshita 2008 | -0.400 -0.597 -0.203 9.34
Kajimoto 2005 | -0.400 -0.583 -0.217 9.39
Suzuki 2009 | -0.200 -0.553 0.153 8.56
Kataoka 2004 | -0.100 -0.363 0.163 9.05
Takashima 2004 | 0.000 -0.540 0.540 7.37
|
theta | -0.549 -0.892 -0.205
------------------+-------------------------------------------------
Overall |
theta | -0.476 -0.774 -0.179
--------------------------------------------------------------------
Heterogeneity summary
-----------------------------------------------------------------------------
Group | df Q P > Q tau2 % I2 H2
---------------+-------------------------------------------------------------
0 | 3 5.07 0.167 0.038 40.85 1.69
1 | 7 163.14 0.000 0.228 95.71 23.31
---------------+-------------------------------------------------------------
Overall | 11 202.10 0.000 0.236 94.56 18.37
-----------------------------------------------------------------------------
Test of group differences: Q_b = chi2(1) = 1.99 Prob > Q_b = 0.159
.
end of do-file
=========================
If you want to try it:
// get the data
import delimited "http://www.robertgrantstats.co.uk/data/cochrane_green_tea_weight_loss.csv", varnames(1) delimiter(",") clear
// calculate the effect size (mean difference, in this case)
meta esize n_tea mean_tea sd_tea n_control mean_control sd_control, ///
esize(mdiff) random(hschmidt) ///
studylabel(study) eslabel("Weight loss (kg)")
// get the MA results
meta summarize, subgroup(japan)
// compare with Analysis 1,4, page 61 in https://www.cochranelibrary.com/cdsr...pub2/epdf/full
sending good wishes to y'all from Hampshire UK
Robert
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