Panel Data Analysis Tutorial - Entering Your Data

Created by Steve Hoover, Modified on Mon, Dec 16 at 2:55 PM by Steve Hoover

Entering Your Panel Data

Panel Data model requires one data block with the following columns:

ID column (first column) that contains a unique number for each row of data.
Target variable which contains the dependent variable for your analysis.
Panel variable which contains a unique numerical or textual identifier for each entity in the data. There should be at least two observations per panel ID (i.e., per unique keyword), and ideally, the number of panel IDs should be reasonably large, say 10 or more.
Time or replication variable which contains a unique numerical or text identifier for each time or replication. The number of replications or time periods per panel ID can be the same (called balanced panel), or they can be different (called unbalanced panel).
Independent variable (at least one). Currently, it is not feasible to analyze two or more panel variables simultaneously.

It is important that the data set contains at least 4 variables (columns) in addition to an ID for each row of the data.

Example Data Set

Below is an example of the necessary format required for Panel Regression analysis. This is the sample OfficeStar data set included when opening the Panel Regression tutorial in Enginius and contains a total of 7 variables available for analysis.

In our example, the following variables are available:

Target variable: Here either Conversions, Clicks, or Impressions could be used as the dependent variable.
Panel variable: Here the panel variable is Keyword, which contains the keywords used in a paid campaign.
Time or replication variable: Here the replication variable is Campaign.
Independent variable:The remaining variables could be the independent variables in the panel regression model. In a model in which Conversions is the dependent variable, Impressions, Clicks, Cost, and Avg Position or a subset of them could be the independent variables. In a model in which Impressions is the dependent variable, the independent variables could be Cost and/or Avg Position.