Hi there. I am a new user of JMP version 16.0. I am using student scores to analyze the prediction scores. I am utilizing the Fit-to-Model. There are data where students are absent during the test. Thus, I leave the score as a character such as 'ABS', set as numeric - continuous at the column setting.
I develop a linear model to analyze the prediction and the results are successfully be calculated by JMP. I wonder how the treatment is carried out for the absent/missing data? I tried to look for a JMP manual to understand the method, but I cannot find any.
There are 2 cases where I'd like to understand the treatment of missing data. Kindly refer attachment for details.
Case 1: When calculating prediction for the current t (t=time) and the absent score is at t time.
Case 2: When calculating prediction for the next t (t=time) and the absent score is during previous t.
The linear model is;
Yijt = Grand mean + <student i> + <subject j> + <(subject*test)jt> + <(student*subject)ij> + εijt
I attach the PDF to explain the simulation, and the operational data for JMP analysis with its results.
Thank you for your help and kind guidance. If there is any beneficial manual or equivalent to understand the treatment, please feel free to share it with me. It is highly appreciated. Thank you.