Baseline variable in regression I am currently looking at this paper:
https://www.nature.com/articles/s41591-021-01487-3
The equation for (1) includes a variable for a baseline value. I am confused as to why they do this as I thought this may cause problems in terms of being correlated with the error term. Any explanation as to why?

It seems like the baseline value $y_{i0}$ in
$$
y_{it} = \beta _0 + \beta _1\rm{High}_i + \beta _2y_{i0} + {{{\boldsymbol{X}}}}_{{{\boldsymbol{i}}}}\beta _3 + \varepsilon _{it}
$$
plays a similar role as an offset in the regression model, though it's not clear to me why they made it a feature rather than an offset. It doesn't differ much from the scenario where you would model $y_{it} - y_{i0}$ as the dependent variable.
