In univariate missing data, where there are missing values for only one variable in a data set, some

In univariate missing data, where there are missing values
for only one variable in a data set, some of the apparently distinct methods
for handling missing data produce identical results for certain statistics.
Consider Table 20.1 on page 612, for example, where data are missing on the
variable X2 but not on X1. Note that the complete-case,
available-case, and mean-imputation estimates of the slope β12
for the regression of X1 on X2 are identical. Prove that
this is no accident. Are there are any other apparent agreements between or
among methods in the table? If so, can you determine whether they are
coincidences?

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