I have little experience with panel data in R, and am trying to run a simple panel regression with the plm-package. When converting my dataframe to a pdata.frame, however, my time index-variable is transformed to a factor variable. This means that if I want to regress a dependent variable as a function of time, the regression generates a long list of dummy-variables for time and calculates individual coefficients for each. I just want the average effect per time unit (ie. average monthly increase/decrease in points).
ID Date Points
1 1/11/2014 2
1 1/12/2014 4
1 1/1/2015 6
1 1/2/2015 8
2 1/11/2014 1
2 1/12/2014 2
2 1/1/2015 3
2 1/2/2015 4
Say the example dataframe structure is ID = int, Date = POSIXct, Points = int. I then convert it to a pdata.frame with index ID and Date:
panel <- pdata.frame(dataframe, c("ID", "Date"))
And run a plm fixed effects regression:
fixed <- plm(Points ~ Date, data=panel, model="within")
The resulting coefficients are then broken down by each month as dummies. I want to treat my time-variable as a continuous variable, so I get only one coefficient for Date. How can I do this? Is there a way to avoid formatting the time index-variable as a factor in panel dataframes?