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imported>Scott (Created page with " ===Purpose=== Create main effect or interaction plot, incl LSD bars. ===Synopsis=== : doeeffectsplot(doe, y, icol, alpha) ===Description=== Main & Interaction Effects...") |
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===Purpose=== | ===Purpose=== | ||
Create main effect or interaction plot, incl LSD bars. | Create main effect or interaction plot, incl LSD bars. | ||
===Synopsis=== | ===Synopsis=== | ||
: doeeffectsplot(doe, y, icol, alpha) | : doeeffectsplot(doe, y, icol, alpha) | ||
===Description=== | ===Description=== | ||
Main & Interaction Effects plots which contain Fisher's Least Significant Difference bars around the mean effect values. | |||
Main & Interaction Effects plots which contain Fisher's Least Significant | |||
====Inputs==== | ====Inputs==== | ||
* ''' | *'''doe''' = DOE dataset object. | ||
*'''icol''' = user selected doe column index. DOE columns are arranged as factors first, then interactions. | |||
:For example: <tt>F1, F2, F3, F1xF2, F1xF3, F2xF3</tt> | |||
*'''alpha''' = 0.05 for two-sided critical region. | |||
*'''y''' = experimentally measured response values | |||
===Example=== | |||
Use [[doegui]] or [[doegen]] to create a doe object, for example with 3 factors (with 2 or more levels) and including 2 term interactions. Then run the following to set up: | |||
<pre>icol=1; | |||
alpha = 0.05; | |||
y = rand(size(doe,1),1); % create y, some expt result values | |||
[doe.data(:,icol) y] % view Factor 1 and y values | |||
%Add the following to make significant difference between F1 groups | |||
y = y + doe.data(:,icol); | |||
doeeffectsplot(doe, y, icol, alpha) | |||
</pre> | |||
===See Also=== | ===See Also=== | ||
[[doegen]], [[doegui]] | |||
[[ | |||
Revision as of 11:14, 12 September 2011
Purpose
Create main effect or interaction plot, incl LSD bars.
Synopsis
- doeeffectsplot(doe, y, icol, alpha)
Description
Main & Interaction Effects plots which contain Fisher's Least Significant Difference bars around the mean effect values.
Inputs
- doe = DOE dataset object.
- icol = user selected doe column index. DOE columns are arranged as factors first, then interactions.
- For example: F1, F2, F3, F1xF2, F1xF3, F2xF3
- alpha = 0.05 for two-sided critical region.
- y = experimentally measured response values
Example
Use doegui or doegen to create a doe object, for example with 3 factors (with 2 or more levels) and including 2 term interactions. Then run the following to set up:
icol=1; alpha = 0.05; y = rand(size(doe,1),1); % create y, some expt result values [doe.data(:,icol) y] % view Factor 1 and y values %Add the following to make significant difference between F1 groups y = y + doe.data(:,icol); doeeffectsplot(doe, y, icol, alpha)