Seeking an efficient way to establish auxiliary time scales refrenced to data elements

[Ray Finucane]

I have been working for 2 + years with data generated from a custom app seeking improvement in treatment of Parkinson's disease. Data are merged from 3 streams, tsset with 1 minute intervals, every day is a panel. Data elements from the app include patient reported symptoms, time, type and quantity of dopamine and related drugs (Rytary and Requip) and other variables. The second stream is biometric data reported by the Apple watch: heart rate, basal and active energy, steps, and the like. The third stream emanates from a Scilab model that estimates concentrations of drugs based on a state space technique.

Drugs are supposed to be taken every 4 hours, at 02 06 10 14 18 and 22 hours, but actual times vary. I seek to establish subpanels based on a new variable aux_axis whose value is zero 60 minutes before a non_zero instance of time_Ry, the time each Rytary is taken, and is 180 120 minutes after actual pill time.

My general approach has been to use subgroup techniques described in Mitchell, MN, "Data Management Using Stata", 2010, Chapter 7, with direct addressing of subscripts, but I haven't succeeded. Is there a better approach to this goal?

[Clyde Schechter]

Maybe somebody else understands and can help you directly, but I am completely baffled by the sentence

I seek to establish subpanels based on a new variable aux_axis whose value is zero 60 minutes before a non_zero instance of time_Ry, the time each Rytary is taken, and is 180 120 minutes after actual pill time.

Can you post a small amount of example data (use the -dataex- command) and then illustrate for a few salient observations what the result you are looking for is?

If you are running version 15.1 or a fully updated version 14.2, -dataex- is already part of your official Stata installation. If not, run -ssc install dataex- to get it. Either way, run -help dataex- to read the simple instructions for using it. -dataex- will save you time; it is easier and quicker than typing out tables. It includes complete information about aspects of the data that are often critical to answering your question but cannot be seen from tabular displays or screenshots. It also makes it possible for those who want to help you to create a faithful representation of your example to try out their code, which in turn makes it more likely that their answer will actually work in your data.



When asking for help with code, always show example data. When showing example data, always use -dataex-.