MCAR auxiliary-variable efficiency ($V_{\mathrm{CC}}-V_{\mathrm{std}}=(1-\rho )\mathrm{Var}(m)/(N\rho )$)

With a fully observed covariate $X$, response $Y$, and an independent response indicator with probability $\rho$, let $m(X)=E(Y\mid X)$. A covariate-standardized mean has asymptotic variance $[\mathrm{Var}(m)+E\{\mathrm{Var}(Y\mid X)\}/\rho ]/N$, whereas the complete-case mean has variance $\mathrm{Var}(Y)/(N\rho )$. The difference is $(1-\rho )\mathrm{Var}(m)/(N\rho )$. Thus missing completely at random does not justify discarding predictive observed covariates on efficiency grounds.