[David Fisher]

Hi Suhail,
Just to say that, for various reasons, the most recent version of metan does not yet have all the changes related to the QE model that we previously discussed (although the code is basically ready). I saw your recent email regarding the paper on double-arcsine, and am happy as ever to work with you to have metan return the most appropriate results.
Sorry for any confusion! I will let you know when the next release is imminent (as soon as possible!! but I am constantly being diverted by more urgent work...) and you can check that everything has been resolved as far as possible.
Regards,
David.

[Suhail Doi]

Hi David,

Thanks - I thought that was the QE update but good to know that it is not and look forward to that.

Yes, the FTT issue as raised may be true but is not really that significant because our simulation runs varying study numbers (per MA) and randomly selecting study size between 1 to 100 events (size=event/p) only brings this up in <1% of pooled meta-analysis results in each run and only at extremes of p so it should be easy to fix.

I don't believe the research community has the option to move away from FTT In meta-analysis as the authors have suggested as the logit transform is really bad at those same extremes of proportions, so even without addressing this, the FTT works better. Once this is fixed then perhaps there will only be the possibility to do a meta-analysis of proportions with metan as I cannot fix this in MetaXL but the caveat is that it does not matter that much.

Regards
Suhail

[dr Mheissen]

Hi David, thanks for this update and your huge efforts.
how can I get the between subgroups p value/Z to check the statistically differences between them?

[David Fisher]

Dear all,

With thanks as ever to Kit Baum, an updated version of metan (v4.06 12oct2022) is now available via SSC.

The following bugs have (hopefully) been fixed:

• Proportion data: fixed bug which caused an exit error when proportion was used with cumulative | influence and with saving() | clear
• Proportion data: proportion with counts now gives the correct denominators for subgroups in the forest plot (they previously appeared doubled)
• When hetinfo(tausq) was used, the value of tau-squared from the first subgroup was repeated across all other subgroups in the forest plot; this has been fixed
• With Quality Effects model, the code has been improved so as to avoid negative weights via rounding error when one or more weights is exactly zero.

Other improvements:

• Added a new option labtitle() to over-ride the default "Subgroup and Study" title with by()
• Minor improvements to the handling and display of zero cells in special cases (e.g. by(), cumulative, influence)
• Major re-ordering of code and subroutines to hopefully improve readability and maintenance going forward. The codebase has effectively been split into three parts: metan.ado, metan_analysis.ado and metan_output.ado; whose respective content should be self-explanatory.

As ever, thanks to all users who have reported issues. In particular, I must apologize if sometimes I do not respond due to workload. When preparing an update, I do try to look back through my correspondence and check that important bug reports or requests have been incorporated. So, please continue to stay in touch!

Best wishes,

David.

[Suhail Doi]

Hi David

I just realized that metan does not report cumulative results in _ES _seES _LCI _UCI when the cumulative option is selected and this is different from what admetan does (which respects whichever option is selected). This makes things very difficult when metan is used within simulations or other ado files so would it be possible to revert back to the former behavior or is there an option to activate this? It also seems logical (at least to me) that these new variables report what the output reports?

Many thanks
Regards
Suhail

[Suhail Doi]

Hi David

With this dataset:

* Example generated by -dataex-. For more info, type help dataex
clear
input str21 study int year str11 location_firstdose int(txanodeath1m txadeath1m planodeath1m pladeath1m) byte qi
"CRASH-2 2010"        2010 "Hospital"    8597 1463 8454 1613 34
"Chakroun-Walha 2019" 2019 "Hospital"      69   27   65   19 28
"CRASH-3 2019"        2019 "Hospital"    3758  855 3622  892 33
"Rowell 2020"         2020 "Prehospital"  563   94  256   53 34
"Guyette 2020"        2020 "Prehospital"  406   41  407   49 35
"PATCH 2023"          2023 "Prehospital"  540  113  498  139 34
end

There is an error when running this code:

metan txadeath1m txanodeath1m pladeath1m planodeath1m  , or qe(qi) study( study )  forestplot(astext(75) textsize(100) boxscale(55) spacing(1.5) leftjustify dp(2) range(0.4 1.3))  extraline(no) hetinfo(isq) by( location_firstdose )

It says:
Error encountered whilst calculating quality weights

Any thoughts?

Regards
Suhail

[Helen Jiahuan He]

Hello,
I ran into an error while I was installing the metan package (please see the screenshot below and the attachment). Basically, I got an error from scc install saying "apparent error in package file for metan" after running the command "ssc install metan, all replace". I am using Stata version 17.0BE, and I also tried Stata version 18.0BE, but I got the same error. I wonder whether someone could help me to address this situation. Thank you very much in advance!


Best,
Helen

[David Fisher]

Suhail Doi : Thanks for this example. The error arises as part of a check that I included in the code, to check that the total weight remains the same before & after the correction detailed in your 2015 CCT paper (which of course should always be the case, mathematically speaking). I have tracked the issue down to a line of code where a variable is not generated in double-precision, so that in this specific example, we see sufficient rounding-error for the error message to be triggered. This will be fixed in the next version. In the meantime, one way to avoid the issue is to run separate models in each subgroup; only "subgroup" calculations are affected by this issue, not "overall" calculations. Apologies!
(P.S. I will contact you separately about the issue you raised back in April in post #50. I have been too busy to respond until recently, but I do have some thoughts on that.)

Helen Jiahuan He . Unfortunately I am unable to replicate this error. Furthermore, if you type ssc describe metan, you can see that the file labbe.ado is listed as part of the package. Could it be a network or firewall issue? Ultimately, I guess the thing to do would be to contact SSC/RePEc via the email address they provide.

Thanks,
David.

[Suhail Doi]

Thanks David for the update in #53. Sounds good and I am glad it was nothing too serious. Look forward to your thoughts on the other issue as I have been working on the 'conclusiveness of meta-analyses' and all methods so far use the CMA results and from that perspective CMA in the main results and saved results seem logical though admetan can be used as well.

Regards
Suhail

[Helen Jiahuan He]

Thank you very much David, somehow there is no such error anymore so the issue has been resolved!

[David Fisher]

Dear all,

With thanks as ever to Kit Baum, an updated version of metan (v4.07 15sep2023) is now available via SSC.

The following bugs have (hopefully) been fixed (among other more minor ones!):

• Proportion data: fixed bug which caused predictive intervals to sometimes be displayed incorrectly (e.g. with subgroups)
• The issue with Quality Effects weights described in post #51 above

Other improvements and changes:

• Implemented "pooled" heterogeneity variance across subgroups (see e.g. Borenstein et al 2009)
• Weights from multiple models can now be displayed in the forest plot and/or saved to the "results set", with new option allweights
• Heterogeneity information display on forest plots is now more clearly arranged, particularly in complex plots e.g. with multiple models. I have also implemented the long-requested change so that the heterogeneity p-value under homogeneity is shown as "p < 0.001" rather than "p = 0.000".
• Alignment of columns of data in forest plots is now handled via mlabpos(), which should hopefully reduce the risk of columns looking "wiggly" (see e.g. https://www.statalist.org/forums/for...text-alignment)
• Due to a subtle but annoying error involving prediction intervals, I have introduced a new value for _USE (_USE==7) specifically for storing prediction interval data. It shouldn't make any obvious difference to how output is displayed.

As ever, thanks to all users who have reported issues -- please continue to do so!


I also presented a poster on metan at this year's Cochrane Colloquium in London earlier this month, and had a few interesting chats as a result. In order to "show off" the capabilities, I put together a series of forest plot examples, some of which were inspired by previous posts here on Statalist, or from email communications -- so thankyou for those. (All data for the examples were taken from published articles!) See our GitHub page here (scroll down to the "Examples" section). If I can find the time, I will try to put up more examples e.g. of particular analyses approaches or use-cases.


Best wishes,

David.

[Suhail Doi]

Hi David,

There is a bug in the subgroup forest plots in the latest version - the heterogeneity estimate in the last subgroup is repeated across previous subgroups but the main output page has the right values (only affects the forest plot). An example is given below where the I2 in the first group is 0%

Regards
Suhail

[Suhail Doi]

Hi David

I figured out where the bug is described in post #57:
The original command used was:

metan lnes lneslci lneshci if smoking !=0 & ma==1,  model(ivhet)  study( studyid )  forestplot(astext(85) textsize(100) boxscale(50) spacing(1) leftjustify range(0.3 2.1) dp(2))  extraline(yes) hetinfo(isq) by(smokcat) eform(HR) noover

When I drop extraline(yes) in the following code then all is well:

metan lnes lneslci lneshci if smoking !=0 & ma==1,  model(ivhet)  study( studyid )  forestplot(astext(85) textsize(100) boxscale(50) spacing(1) leftjustify range(0.3 2.1) dp(2)) hetinfo(isq) by(smokcat) eform(HR) noover

Regards
Suhail