Use the link method twice to connect the data from African nations (continent 1 and continent 2). Subtract the results to get the extended difference of log GDP.

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In this model, we can see the PI is no longer 95%. Instead, it is 97%, which means we are talking about Bayesian statistics, and the posterior probability has changed.

Example: Use Bayesian Methods to Find the Association between Ruggedness and log GDP of Nations in Africa

McElreath, R. (2020). Statistical Rethinking: A Bayesian Course with Examples in R and STAN (2nd ed.). Chapman and Hall/CRC.

Statistical Rethinking: A Bayesian Course with Examples in R and STAN (2nd edition)

How to Build this Model

There is no raw data here. We are just building the model with existed models, then compared the difference. 
Although there might be a deeper reason for the log GDP in Africa, the association between log GDP and ruggedness might help us to come up with some methods to improve current situation.

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