st: RE: RE: Using the metan command

[Amal Khanolkar <Amal.Khanolkar@ki.se>]

Hi Carole,

Thanks for the suggestion!

I've got it to work...  :) 

But however it seems to run only if I include a smaller part of my dataset with say 9 RR. If I run it on a dataset with 66 RR, I get the follwoing error msg:

 metan rr lci uci
Effect size and confidence intervals invalid:
order should be {effect size, lower ci limit, upper ci limit}
r(9);


The dataset:
input id rr lci uci group

            id         rr        lci        uci      group
  1. 1 1.12 0.78 1.62 2
  2. 2 0.96 0.83 1.30 2
  3. 3 0.96 0.85 1.09 2
  4. 4 0.84 0.65 1.07 3
  5. 5 0.98 0.90 1.07 3
  6. 6 0.95 0.88 1.02 3
  7. 7 1.11 0.69 1.80 4
  8. 8 1.08 0.90 1.30 4
  9. 9 0.85 0.73 0.97 4
 10. 10 1.76 1.24 2.50 5
 11. 11 1.15 0.98 1.34 5
 12. 12 0.86 0.75 0.99 5
 13. 13 1.57 1.31 1.87 6
 14. 14 0.90 0.82 0.97 6
 15. 15 1.07 1.01 1.14 6
 16. 16 0.86 0.51 1.45 7
 17. 17 0.95 0.80 1.14 7
 18. 18 1.31 1.16 1.47 7
 19. 19 1.30 1.00 1.70 8
 20. 20 0.98 0.88 1.10 8
 21. 21 0.76 0.70 0.83 8
 22. 22 0.99 0.71 1.40 9
 23. 23 0.90 0.80 1.04 9
 24. 24 0.91 0.81 1.01 9
 25. 25 1.27 0.81 2.00 10
 26. 26 0.74 0.60 0.93 10
 27. 27 2.57 2.31 2.86 10
 28. 28 0.87 0.52 1.44 11
 29. 29 0.84 0.70 1.00 11
 30. 30 0.70 0.60 0.82 11
 31. 31 0.99 0.76 1.28 12
 32. 32 0.96 0.87 1.06 12
 33. 33 0.99 0.91 1.07 12
 34. 34 1.67 1.30 2.14 13
 35. 35 1.06 0.94 1.12 13
 36. 36 0.68 0.62 0.76 13
 37. 37 1.52 1.07 2.16 14
 38. 38 1.62 1.42 1.84 14 
 39. 39 0.67 0.58 0.77 14
 40. 40 1.27 0.87 1.85 15
 41. 41 0.85 0.71 1.02 15
 42. 42 1.85 1.67 2.04 15
 43. 43 1.51 1.08 2.10 16
 44. 44 1.20 1.06 1.36 16
 45. 45 0.43 0.37 0.50 16 
 46. 46 1.53 0.92 2.55 17
 47. 47 0.88 0.72 1.13 17
 48. 48 0.74 0.60 0.90 17
 49. 49 0.60 0.34 1.02 18
 50. 50 1.10 0.94 1.28 18
 51. 51 0.62 0.53 0.72 18
 52. 52 2.03 1.32 3.12 19
 53. 53 1.31 1.08 1.60 19
 54. 54 0.90 0.74 1.08 19
 55. 55 1.56 1.45 1.67 20
 56. 56 1.02 0.99 1.05 20
 57. 57 0.93 0.91 0.96 20
 58. 58 1.10 1.01 1.21 21
 59. 59 1.07 1.03 1.11 21
 60. 60 0.93 0.82 0.91 21
 61. 61 1.55 1.35 1.77 22
 62. 62 1.01 0.95 1.07 22
 63. 63 0.86 0.82 0.91 22
 64.  end

Is there a limit on the number of RR that can be included when using metan? 

Thanks,

/Amal 

________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Khairallah, Carole [khaicar] [Carole.Khairallah@liverpool.ac.uk]
Sent: 09 July 2013 12:21
To: statalist@hsphsun2.harvard.edu
Subject: st: RE: Using the metan command

Hi Amal,

Your error comes from the fact that you have 1 data line with value 0 as lower and upper CI.
If you remove this observation, your command will work.

To make the forest plot stratified by e_group, just add in the options: by(e_group)

One option:

metan rr lci uci, ///
        nosecsub sgweight ///
        by(e_group)   ///
        effect(Risk ratio in ... ) ///
        dp(2) boxsca(30) aspect(0.8) astext(80) textsize(140)


Good luck


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Amal Khanolkar
Sent: 09 July 2013 12:02
To: statalist@hsphsun2.harvard.edu
Subject: st: Using the metan command

Hi all,

Some issues with using the metan command. I've read the help file for the same, but I need some help in better understanding how I use this command.

I have a small dataset as follows:

input id rr lci uci e_group

1 1 0 0 1

2 1.12 0.78 1.62 2
3 0.96 0.83 1.30 2
4 0.96 0.85 1.09 2

5 0.84 0.65 1.07 3
6 0.98 0.90 1.07 3
7 0.95 0.88 1.02 3

8 1.11 0.69 1.80 4
9 1.08 0.90 1.30 4
10 0.85 0.73 0.97 4

11 1.76 1.24 2.50 5
12 1.15 0.98 1.34 5
13 0.86 0.75 0.99 5

14 1.57 1.31 1.87 6
15 0.90 0.82 0.97 6
16 1.07 1.01 1.14 6

17 0.86 0.51 1.45 7
18 0.95 0.80 1.14 7
19 1.31 1.16 1.47 7

20 1.30 1.00 1.70 8
21 0.98 0.88 1.10 8
22 0.76 0.70 0.83 8


The five variables above are:  ID, risk ratio (rr), lower confidence limit, upper confidence limit, and ethnic group. In effect it is three RRs for three outcomes for each ethnic group obtained from a multinomial logistic regression model, which I would like to show using a forest plot.

Just to get a basic forest plot I typed:

metan rr lci uci

But I get this in response:

Effect size and confidence intervals invalid:
order should be {effect size, lower ci limit, upper ci limit}


So, I'm not sure if I have to provide the weights as part of the above command to get it to work? If so, how do I generate the weights? This is not a true meta-anaylsis that I'm trying to plot, but just relative risks from a multinomial logistic regression model. Ideally I would also like to group the RR according to the grouping variable above.

Thanks!

/Amal
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