395203_en-US

liliconcom

Controlling nominal 2-level factor coding

Greetings,

 

I'm having trouble understanding JMP's coding of a simple 2-level factorial design. The (-1,1) levels of the coding table created by Fit Model (Standard Least Squares, Effect Screening) appear reversed from the design table Pattern and associated column Value Orders.

 

I've attached an example design with factor levels named to keep track of low and high levels (Full Factorial-Nom.jmp). Three factors are character/nominal and the one is numeric/nominal just to see if it is treated differently. The design pattern column correctly identifies the levels, and the Value Order property for each column is also correct. So far so good...

 

After fitting a main effects model, the levels of the coding table are reversed. I've attached the result with the original pattern column pasted in for reference (Coding Table-Nom.jmp). I know that the model will be mathematically correct with signs reversed but I find it to be a nuisance in practice, especially on larger and more complex fractional designs where I often use coded levels for diagnostics, exporting to other software, etc.

 

I note the coding attribute in the data table is inaccessible for nominal column types. Why is that? I can reverse the column value orders to code correctly but then, of course, plotting levels are reversed. Am I missing something obvious here? I've looked at documentation and other threads before posting.

 

Thanks for any insights - 

 

- Tom

Data TableDOERe: Controlling nominal 2-level factor coding

Sorry, I don't think I understand your question.  Desired coding of the factors is equi-distant centered on zero. This historically accounts for the likelihood that parameter estimates will need to "compensate" for differences in level values thus making it difficult to compare the estimates.  Coding "normalizes" the parameter estimates.  Now, it is done in the background whether you code or not.  Coding of categorical factors (Joe and Mike for example) is arbitrary.

 

What I don't understand is when you analyze the dataset using fit model, you don't change the dataset whatsoever.  You don't get a new table when you do the analysis.  So I don't understand how or why you created the second dataset?

Re: Controlling nominal 2-level factor coding

Thanks. Actually, I'm not questioning the need or reasons for coding, or the different parameterizations that are used for various contrasts. I'm after something simpler since I often use the model coding as well as the named factor table. For the two-level case using the sum-to-zero contrasts, why doesn't JMP use the intuitive (-1) for the "lower" factor levels and (+1) for the "higher" levels that are defined in the design data table? And is there a way to force that? 

 

Thanks,

 

- Tom

Re: Controlling nominal 2-level factor coding

Sorry, I'll have to let someone else answer as I am still confused by the question. Which is higher Joe or Mike? Which is higher green or red? These are arbitrary, there is no logical ordering to the coding. Are you having difficulty interpreting the parameter estimates?  You can specify what level is which in the design of the experiment when you add the factors.

Re: Controlling nominal 2-level factor coding

---

@statman wrote:

Sorry, I'll have to let someone else answer as I am still confused by the question. Which is higher Joe or Mike? Which is higher green or red? These are arbitrary, there is no logical ordering to the coding. Are you having difficulty interpreting the parameter estimates?  You can specify what level is which in the design of the experiment when you add the factors.

---

Just to clarify for anyone who'd like to look at this. As statman notes, I did specify the factor levels when adding the factors and creating the design. The "Pattern" column JMP created confirms that these levels were established. I also used "Low" and "High" in the factor level names to make them "non-arbitrary" for the purpose of interpreting this example. So the design is fine for my purpose. See attached design table in opening post. My question is not about the design, but rather about why the modeling platform codes it in a way that is inconsistent with the design levels as established. That is, why are the coding matrix (-1,1) signs reversed from the design?

 

- Tom