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Purpose:

ei gives observation-level estimates (and various related statistics) of $\beta^b_i$ and $\beta_i^w$ given variables $T_i$ and $X_i$ ( $i=1,\dots,n$) in this accounting identity: $T_i = \beta^b_iX_i + \beta^w_i(1-X_i)$. Results are stored in dbuf, a data buffer that should be read with eiread or graphed with eigraph. See the model in Chapter 6, and extensions in Chapter 9.