how to obtain scatter plot of age- and gender-adjusted biomarker X vs motor severity score Y using JMP

[#1]

We would like to clarify whether there is a linear relationship between biomarker X and motor severity score Y in patients with a neurological disorder. Since age and biological sex influence the biomarker X, we considered them as covariates. We estimated the association between variables using partial Pearson correlations, and linearly adjusted for the effects of age and gender. We would appreciate it very much if you could let us know how to obtain scatter plot of age- and gender-adjusted biomarker X vs motor severity score Y using JMP.

[#2]

It's not 100% clear to me what you mean by '...linearly adjusted for the effects of age and gender...', but I'll assume you modified biomarker X values in some fashion? If that's the case, why can't you just use the adjusted biomarker X variable as an 'x' variable and the motor severity score as the 'y' in say Graph Builder? Just for grins you could also show all 4 'x' variables and the motor severity score in the Multivariate platform as a matrix of scatter plots. That might look really interesting?

[#3]

Thank you for your reply. 

This may be a simple question, but we would appreciate it if you could give us your opinion on how to adjust the variables by age and gender.

[#4]

The question may be simple in that you want my opinion...but I'm very reluctant to share it without knowing much more about:

1. The domain in which the problem resides...process knowledge comes first and WAY before analysis.

2. How repeatable and reproducible is the measurement system?

3. How was the data collected? Pathways could be...a designed experiment, happenstance/observational (what were the sampling protocols, exclusions, limitations, etc.), a homework assignment (in which case I don't want to get you in trouble with your professor...) out of a book, a research study that will be influenced by regulatory/compliance requirements...and many more.

4. What's the purpose of the study from a Deming enumerative vs. analytic perspective?

5. On a more mechanical side...what version of JMP are you running? This influences what is possible from a data analysis perspective since there are major differences between JMP, JMP Pro, JMP Clinical, and JMP Genomics...and from what little you have provided so far...any one of these JMP products might have just the right capabilities.

[#5]

OK.Below is the answer to your question

1. The domain in which the problem resides...process knowledge comes first and WAY before analysis.

→OK.

2. How repeatable and reproducible is the measurement system?

→It is unclear how reproducible it is, but there is a correlation between the explanatory variables and the dependent variables. I would like to try adjusting by age and gender.

3. How was the data collected? Pathways could be...a designed experiment, happenstance/observational (what were the sampling protocols, exclusions, limitations, etc.), a homework assignment (in which case I don't want to get you in trouble with your professor...) out of a book, a research study that will be influenced by regulatory/compliance requirements...and many more.

→observational 

4. What's the purpose of the study from a Deming enumerative vs. analytic perspective?

→I want to see the correlation between the explanatory variables and the dependent variables, but at that time I want to adjust the explanatory variables according to age and gender. I want to output the adjusted variable.

5. On a more mechanical side...what version of JMP are you running? This influences what is possible from a data analysis perspective since there are major differences between JMP, JMP Pro, JMP Clinical, and JMP Genomics...and from what little you have provided so far...any one of these JMP products might have just the right capabilities.

→JMP