Constrained variables query

[#1]

Hi,

Can anyone advise a simple way to indicate that either a factor or an effect is constrained within limits ?  Examples would include numbers expressed as %'s which must therefore lie between 0 & 100, such as Purity or the Yield of a reaction.  This would be especially useful if it can be applied to a data table column, for example, rather than needing to be built into a custom design, thus enabling the simpler methods of fitting models such as Full Factorial or Response Surface

Thanks

Nick

[#2]

Check out the column property, "Response Limits".  

     Help

and then search on Response Limits

[#3]

Thanks for the suggestion.  I have taken a look at the options available from the drop-down menus in the Column Properties field (there are a lot of them !).  Also I have referred to the Help.  At least from the latter perspective the only clear instruction (to me) is that this is a way of setting the desireability of an outcome in terms of High and Low values.  So, whilst this might reject an outcome of -1 or +101 as being unfit to meet the targets set, it would not actually influence the modelling process that could generate such numbers,  I am no statistician, but I can remember from courses I took long ago that there are "special" ways of treating variables which are "bounded" - so whilst for example you might expect to find a Gaussian distribution of values either side of (for example) a solution being made up with a target of 50% concentration, if the target is changed to 100%, the distribution curve would look like one half of the normal bell curve, as its impossible (other than by measurement error) to get a value above 100%. 

There may be something yet to be found in JMP on this matter, but frankly I don't find the Help very helpful - its good to have the Community as an alternative, so thanks again for pointing out this option.

[#4]

Or maybe the Range Check column property?

[#5]

Thanks for the suggestion, but according to the Help entry for Range Check, this simply alerts to (or excludes) numbers that lie outside a predefined range for data entry  This is fine for alerting to a typo or an excel formula error (for example) but does not reflect the position from a statistical analysis perspective.  ie the model will still be constructed in terms of predictions below 0 or above 100 (% purity), even though such values these are meaningless numbers, nd cannot be attained in practice (other than by measurement uncertainty) - just as length is a continuous variable, except that its impossible to have a negative length.