I have gathered data from 60 companies, across 5 years.
I want to do a Multiple Linear Regression Analysis with some variables, from 2017 to 2021.
1) Should I do the average of the 5 years for each variable for each company, and do the regression, having 60 observations, or
2) Should I threat the data as individual points, meaning observations = n*5 = 300
How do I display that information (colums and rows), on the excel sheet (if option 2)?
Thanks a lot
Do not average, but use a multi-level model with company-level random effects. Also, you should examine how time itself influences your outcome directly. In one of the R regression engines (lme4, rstanarm, brms), the model would look like this:
outcome ~ 1 + time + pred_1 + pred_2 + (1 + time + pred_1|Company)
In this model, all companies get their own slope over time. Pred_1 is also estimated on populatio-level and per individual company. Pred_2 is an example of a pure population-level effect (aka fixef effect). That is useful for predictors that do not vary within one company, such as the country of residence.
To estimate multi-level models, you'll have to bring your data into long-format (one outcome measure per row), e.g.:
CompID | Pred_1 | Pred_2 | time | outcome
Hope that helps, if not: https://schmettow.github.io/New_Stats/mlm.html
Get a copy of Kuttner et al applied linear statistical models 5th Ed and read it. David Booth
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