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 <[email protected]>
Reply-To: [email protected]
Organisation: INLogic Ltd
To: <[email protected]>
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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