I have the following data:
Code EBP EBM Genre Experience Zone Time 1 4.35 4.83 0 5 0 1 2 4.2 4.1 1 5 0 1 ... 1 3.8 4,23 1 0 5 2
And I am tasked with creating a linear regression to predict the values EBP (this is a scale from 0-5 that measures the satisfaction with the company) and EBM (also a 0-5 scale that measures the satisfaction with the clients) of the whole staff. It has been measured two times for each individual defined by the variable time with values 1 and 2. From previous experiences with similar data I've been told that the model would be linear and I have two measurements so I thought doing a paired repeated measures.
What I am trying to do is create a linear model where I can predict and measure the impacts of genre, Experience, Zone and so on. I´ve alredy done t-test and d-cohen to try to measure the impact.
I am not that experienced so I feel I am confusing thing and tried porgramming :
empleo.nested<-lmer( EBP~ ns(Time, 2) * Experience + Genre + (Time | Genero),data = Empleo)
But I feel I am missing things, also tried de ezAnova but it is not quite working out because of NAs.
Any help is deeply appreciated