I would like to forecast the probability of a binary outcome using logistic regression at t+1, using all previous data points. I am new to forecasting so any help would be appreciated.
The raw data is in the form:
Time | Correct 1 0 1 1 2 1 3 0 3 0 3 1 4 1 5 0
I have averaged the data over each day to produce:
Time | AVG. Correct 1 0.5 2 1 3 0.3 4 1 5 0
I know that there is a linear trend in the data, such that as time progresses the average correct value increases.
Using this information would it be possible to use logistic regression to forecast the next time step (t = 6). How would you account for the linear trend in the data for a logistic regression model?.