[David Fisher]

Hi Nicoletta Riva ,

Thankyou for your message. I have received communication from another user recently, using Stata 13, who reported the same problem. I'm fairly sure the reason is a subtle change to the way Stata works, made at the time of Stata 14. This means that -metan- currently does not work properly with Stata 13 and below -- many apologies for this!! Thankfully the solution is simple, and I will be releasing an update very soon.

In the meantime, if you have some urgent work to complete, let me know and I will try to help (e.g. I can create the plot at my end if you are happy to share the data, and/or I can send you an "unofficial" updated version of the code.)

Best wishes,

David.

[Nicoletta Riva]

Hi David,

Nice package the updated metan!
I especially like the inclusion of metaprop.

I have tried metan both with proportion and with rr, I get the tables and the stats correctly, but I do not manage to create the forest plots (I am using STATA 12).

Just to give you an example, this is my dataset:

* Example generated by -dataex-. To install: ssc install dataex
clear
input str14 study byte(deadGrp1 totalGrp1 deadGrp2 totalGrp2) float(aliveGrp2 aliveGrp1)
"study1" 1 15 5 20 15 14
"study2" 2 60 4 64 60 58
"study3" 3 22 3 24 21 19
"study4" 4 36 2 40 36 32
"study5" 5 45 1 44 43 40
end

these are the two commands that I am running:

metan deadGrp1 totalGrp1, proportion random ftt lcols(study) counts forestplot

or

metan deadGrp1 aliveGrp1 deadGrp2 aliveGrp2, rr random lcols(study) forestplot

in the first case, I get

Studies included: 5
Participants included: 178

Meta-analysis pooling of Freeman-Tukey transformed Proportions
using the random-effects inverse-variance model
with DerSimonian-Laird estimate of tau²

--------------------------------------------------------------------
study                | Proportion  [95% Conf. Interval]   % Weight
---------------------+----------------------------------------------
study1               |     0.067      0.012     0.298       8.80
study2               |     0.033      0.009     0.114      33.01
study3               |     0.136      0.047     0.333      12.70
study4               |     0.111      0.044     0.253      20.34
study5               |     0.111      0.048     0.235      25.15
---------------------+----------------------------------------------
Overall, DL          |     0.077      0.038     0.125     100.00
--------------------------------------------------------------------

Test of overall effect = 0:  z =   5.597  p = 0.000


Heterogeneity measures, calculated from the data
with Conf. Intervals based on Gamma (random-effects) distribution for Q
---------------------------------------------------------
Measure              |     Value      df      p-value
---------------------+-----------------------------------
Cochran's Q          |      4.13        4      0.389
                     |            -[95% Conf. Interval]-
H                    |     1.016     1.000     1.695
I² (%)               |      3.0%      0.0%     65.2%
---------------------------------------------------------
H = relative excess in Cochran's Q over its degrees-of-freedom
I² = proportion of total variation in effect estimate due to between-study heterogeneity (based on Q)


Heterogeneity variance estimates
-----------------------------------
Method               |     tau²
---------------------+-------------
DL                   |    0.0002
-----------------------------------
invalid syntax
Error in metan.BuildResultsSet
(Note: meta-analysis model was fitted successfully)
r(197);

it gives Error in metan.BuildResultsSet and does not produce the forestplot. Same error in the second case.

I was wondering what is my mistake. Do you have any suggestions?

Thanks in advance!

Nicoletta

[Suhail Doi]

Hi David,

Thanks for sorting out the earlier issue so quickly!

Another more complicated request - feel free to ignore :-)

I note that proportions have been added to the metan suite and the Freeman-Tukey double arc sin transformation implemented. Also I note that you used the Schwarzer et al implementation of the Miller back transform that uses the harmonic mean [1]. They illustrate the issues with this implementation using the dataset below:

* Example generated by -dataex-. To install: ssc install dataex
clear
input str3 studyname long n int cases
"S1"  217154 422
"S10"  16557  32
"S13"    676   1
"S18"     44   1
"S26"     29   1
end

and report a 0 (0, 0) RE result which also is reported by metan and is counter-intuitive. MetaXL reports the RE result from this dataset as:

0.199%

(0.137%,

0.272%)

using the same transformation. The difference is because after extensive simulations we realized that for meta-analysis we should use 1/V in place of use of harmonic N for back conversion as that was not meant for meta-analysis [2]. However, we must use the simple back-conversion, (SIN(t/2))^2, when P/V or (1-P)/V) is less than 2 to avoid the back-transform from bombing out [V is FTukey pooled variance t is the FTukey pooled proportion and P is the simple back transformed proportion given by (SIN(t/2))^2) ]. Thus based on the values P/V or (1-P)/V the Miller back transform is either used (but N replaced by 1/V) or the simple back transform , P, is retained. For the CI's, we replace the lower by 0 if P/V<2 (otherwise go for the modified Miller backtransform) and the upper by 1 if (1-P)/V <2 (otherwise go for the modified Miller back-transform). All this is explained in our paper [2].

Would it be possible to add the MetaXL implementation as an option (I can confirm through extensive simulations that it outperforms all other options) Also we use the variance of the transformed proportion for individual studies as 1/(N+0.5) and not what has been reported by Schwarzer et al and that will be needed to pair with this option if you decide to add this as documented in our paper [2].

Regards
Suhail

References

1. Schwarzer G, Chemaitelly H, Abu-Raddad LJ, Rücker G. 2019. Seriously misleading results using inverse of Freeman-Tukey double arcsine transformation in meta-analysis of single proportions. Research Synthesis Methods 10: 476–483.

2. Barendregt JJ, Doi SA, Lee YY, Norman RE, Vos T. Meta-analysis of prevalence. J Epidemiol Community Health. 2013 Nov 1;67(11):974-8

[Suhail Doi]

Hi David,

That's right, admetan works fine

Many thanks

Suhail

[David Fisher]

Hi Suhail,
Ah, I knew someone would find a bug sooner or later :-)
Thankyou, I'll look into it. I assume this doesn't happen with admetan?
Best wishes,
David.

ETA: It was a very simple fix! I'll see what other communication I receive, but I'll try and get a small update available very soon. Sorry again!

[Suhail Doi]

Hi David,

Thanks for this very useful package update. I tried the QE model on the data below:

* Example generated by -dataex-. To install: ssc install dataex
clear
input str23 study int n byte(a b c) int d float qi byte(q1 q2 q3 q4 q5) float(r1 r2 r3 r4 r5)
"Baronciani (1986) [24]"   74 13  4  8  49 .29166666 43 64 45 46 53 3.5   6 3.5   8   7
"Dura (1997) [25]"         48  3  4 14  27         1 86 89 85 77 79  12  12  12  12  12
"Evans (1999) [26]"       113  2 10 17  84  .5833333 50 68 48 42 49   7 7.5   5 4.5   4
"Foresman (2001) [27]"    139 24 43 25  47  .9166667 79 82 79 73 76  11  11  11  11  11
"Mage (1989) [28]"        122 22  5 19  76 .08333334 36 57 42 35 42   1 1.5 1.5   1   1
"Mahant (2002) [29]"      162 14 30 21  97  .8333333 64 75 73 65 68  10  10  10  10  10
"Morin (1999) [30]"        70 20 41  2   7  .5833333 50 68 55 42 52   7 7.5   7 4.5 5.5
"Muensterer (2002) [31]"  386 35 76 34 241       .75 57 71 58 46 55   9   9 8.5   8   8
"Oostenbrink (2000) [32]" 140 21 20 16  83 .29166666 43 61 42 42 47 3.5   4 1.5 4.5   3
"Salih (1994) [33]"        42 26  3  1  12 .29166666 43 57 52 46 58 3.5 1.5   6   8   9
"Tan (1988) [34]"          55  3  6 14  32  .5833333 50 61 58 42 52   7   4 8.5 4.5 5.5
"Verber (1988) [35]"       62  8  9 20  25 .29166666 43 61 45 38 46 3.5   4 3.5   2   2
end

using the following code:

metan a b c d,  qe(q3) study( study ) or counts forestplot(astext(85) boxscale(65) spacing(0.95) leftjustify)

The forestplot does not display and the following error displays:

option qwt() not allowed

Error in forestplot

Any thoughts?

Regards
Suhail