Ok I see now — those are just the predicted values. So if you are predicting crime counts over time for an example, in that graph at time period 15, the red line has close to a predicted 4 crimes per year.

Always feel free to send me an email Celina — apwheele@gmail.com.

]]>I am trying to figure out how to read the first graph that is created when I run the line plot(out1). I know the x-axis is the time, but what about the y-axis?

]]>I’m not sure what code you are referring to — can you be more specific?

]]>I was wondering exactly what does the muhat(time) axis means?

]]>So just reading the pubmed paper, your gen total_row works out as the individual person measure of entropy. For that measure they do not do any group metrics, that one is just for individuals, so the by part doesn’t make sense.

Haven’t read the other papers. Lower values are definitely better, but the pubmed article gives examples where it doesn’t work out so well. (If folks are saying higher values are better, make sure they are calculating the negative in front of the entropy measure, if not then closer to 0 will be better.)

It would take more work to implement the pubmed article suggested hypothesis testing approach. So I won’t be taking that on anytime soon.

]]>I see that some have asked you about the “entropy”. According to the is paper it’s a suggested measure to assess the discrimination between the groups (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4254619/)

I tried to calculate the entropy for a model with 3 classes as follow (Excuse the primitive way of coding)

gen log_grob1 = ln(_traj_ProbG1)

gen log_grob2 = ln(_traj_ProbG2)

gen log_grob3 = ln(_traj_ProbG3)

gen total_row= (-1*(_traj_ProbG1*log_grob1 + ///

_traj_ProbG2*log_grob2 + ///

_traj_ProbG3*log_grob3)/ln(3))

bys _traj_Group : summ total_row

Q1: do you think my approach of calculating this “entropy” correct ?!

Q2: Also I’m not sure about the threshold, the paper mentioned above suggest a lower value of entropy is better, and other empirical papers suggest higher values are better (i.e. https://journals.sagepub.com/doi/full/10.1177/0081246317721600

https://psycnet.apa.org/record/2010-22993-004

https://link.springer.com/article/10.1007/s00420-017-1277-0)