Hi Ross,
Many thanks greatly for you help, your suggestions work ok together. I
also chose to express observations as fractional effects rather than
percentage effects which lets the plot show estimates of effect sizes
without the excessive number of decimal places.
I'm glad too that you found something in this to take away for possible
further revision of metan.
Kind regards,
Geoff. L.
-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Ross Harris
Sent: 12 March 2007 12:13
To: statalist@hsphsun2.harvard.edu
Subject: st: How do we format data and place the graphic in metan?
Hi
Regarding the placement of the graphic, I am afraid that this is fixed
and cannot be changed- the plot is always placed between the left and
right columns of data. If you have one or two particularly extreme
estimates/confidence intervals that are causing a lot of graph space to
be wasted, you could however use _xlabel(#,#,#...) and _force. This will
mean your confidence intervals are truncated in the display, but would
allow more space for the rest of the data. Note also that metan may
display symmetric x-axes either side of the null effect line- using
these options can also rectify that.
As to the excessive number of decimal places, this could be fixed
quickly by making the data into strings. Consider:
gen treatdose2 = string(treatdose, "%5.3g")
This will control the number of decimal places used as a column in
metan. I will keep a note of this however as this is something we may
want to make easier in the next update- so thanks!
Hope this helps,
Ross
-------- Original Message --------
Subject: st: How do we format data and place the graphic in
metan ?
Date: Sat, 10 Mar 2007 11:20:57 -0000
From: G Livesey <glivesey@inlogic.co.uk>
Reply-To: statalist@hsphsun2.harvard.edu
Organisation: INLogic Ltd
To: <statalist@hsphsun2.harvard.edu>
I looking to improve the formatted output in the graphic of 'metan' in
v9.
I am having two problems:
1. I would like to move the central graphic right or left without moving
the columns of information/data. If I could do this I would be able to
make better use of the space within the overall graphic, and so more
clearly illustrate the results.
2. I would also like to format the columns of data in the graphic. In
particular to format the data as X.Y where X and Y are specified at
any reasonable length about the decimal point (at present I get too many
significant places). Formatting the input data doesn't affect the output
in the graphic (or so it appears).
I feel to have exhausted my exploration of metan on these problems with
only the following seemingly related information, perhaps because the
update to metan is so recent (and helpful!!)
http://www.stata.com/statalist/archive/2007-02/msg00748.html.
Possible the answer is quite basic, however I have not yet stumbled on
solutions during my exploration. The code and data showing need of some
formatting in the overall graphic is given below.
What tricks am I missing? I should be grateful for potential solutions.
With thanks
Geoff Livesey
#delimit;
metan theta theta_se , by(group_1) random second(fixed) rfdist
label(namevar = source)
xtitle("Percentage attenuation", size(*0.5))
xlabel (-40 , 0)
plotregion(style(none))
graphregion(color(white))
astext(60)
lcols(source treatdose)
favours(Better # Worse)
;
#delimit cr
| source theta theta_se
group_1 treatd~e |
|-----------------------------------------------------------------------
|----
--------------------------------|
1. | Kawasaki et al 2000 (B) -21.2 14.69924 Cases with
higher carbohydrate tolerance 6.30 |
2. | Kishimoto et al 2000 (B) -3.1 3.209351 Cases with
higher carbohydrate tolerance 4.60 |
3. | Mizushima et al 1999 (B acute) -33.2 21.48279 Cases with
higher carbohydrate tolerance 9.80 |
4. | Shinohara et al 1999 (B) -8.2 11.35006 Cases with
higher carbohydrate tolerance 5.00 |
5. | Shioda et al 2001 (B n20) -18.2 19.74265 Cases with
higher carbohydrate tolerance 7.90 |
|-----------------------------------------------------------------------
|----
--------------------------------|
6. | Tokunaga & Matsuoka 1999 (B) -8.4 3.329585 Cases with
higher carbohydrate tolerance 5.10 |
7. | Unno et al 2002 (B S) -13.6 7.523515 Cases with
higher carbohydrate tolerance 5.20 |
8. | Uno et al 1999 (B) 8.6 28.70391 Cases with
higher carbohydrate tolerance 5.00 |
9. | Wakabayashi et al 1999 (A roll) -37.1 2.603687 Cases with
higher carbohydrate tolerance 7.00 |
10. | Ueda et al 1993 (30g acute) -4.8 6.649664 Cases with
mixed carbohydrate tolerance 30.00 |
|-----------------------------------------------------------------------
|----
--------------------------------|
11. | Ueda et al 1993 (3g acute) -12.7 5.249016 Cases with
mixed carbohydrate tolerance 3.00 |
12. | Ueda et al 1993 (6g acute) -16.3 5.630603 Cases with
mixed carbohydrate tolerance 6.00 |
13. | Wakabayashi 1992 -7.4 4.505731 Cases with
mixed carbohydrate tolerance 30.00 |
14. | Wakabayashi et al 1999 (glu) -7.7 8.08934 Cases with
mixed carbohydrate tolerance 10.00 |
15. | Wakabayashi et al 1999 (md) -21.8 9.395063 Cases with
mixed carbohydrate tolerance 10.00 |
|-----------------------------------------------------------------------
|----
--------------------------------|
16. | Wakabayashi et al 1999 (ndl) -23.5 3.00385 Cases with
mixed carbohydrate tolerance 5.00 |
17. | Wakabayashi et al 1999 (su) -25.1 2.142058 Cases with
mixed carbohydrate tolerance 10.00 |
18. | Wolf et al 2001 -3.7 3.452281 Cases with
mixed carbohydrate tolerance 16.00 |
19. | Kawasaki et al 2000 (A) -18.5 10.54169 Cases with
lower carbohydrate tolerance 6.30 |
20. | Kishimoto et al 2000 (A) -19.5 2.582998 Cases with
lower carbohydrate tolerance 4.60 |
|-----------------------------------------------------------------------
|----
--------------------------------|
21. | Mizushima et al 1999 (A acute) -23.1 17.36217 Cases with
lower carbohydrate tolerance 9.80 |
22. | Shinohara et al 1999 (A ) -11.7 10.27774 Cases with
lower carbohydrate tolerance 5.00 |
23. | Shioda et al 2001 (A n20) -11.0 15.70164 Cases with
lower carbohydrate tolerance 7.90 |
24. | Tokunaga & Matsuoka 1999 (A) -31.7 2.466213 Cases with
lower carbohydrate tolerance 5.10 |
25. | Unno et al 2002 (A ~prone S) -22.0 3.550336 Cases with
lower carbohydrate tolerance 5.20 |
|-----------------------------------------------------------------------
|----
--------------------------------|
26. | Uno et al 1999 (A) -7.7 15.79408 Cases with
lower carbohydrate tolerance 5.00 |
27. | Wakabayashi et al 1999 (B roll) -48.1 3.576585 Cases with
lower carbohydrate tolerance 7.00 |
+-----------------------------------------------------------------------
+----
--------------------------------+
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