\begin{Schunk}
\begin{Sinput}
 df2.1 <- as.data.frame(mi.inference(betas, se.glm))
 df2.2 <- cbind("MI",df2.1[,1:2], "LD", ldbeta = coef(ldglm), ldse = sqrt(diag(vcov(ldglm))), "full", est = coef(fullglm))
 df2.2
\end{Sinput}
\begin{Soutput}
            "MI"   est std.err "LD" ldbeta  ldse "full"    est
(Intercept)   MI  2.89  0.4254   LD  5.900 0.925   full  4.522
pclass2nd     MI -0.91  0.2682   LD -2.111 0.523   full -1.495
pclass3rd     MI -2.10  0.2799   LD -4.478 0.763   full -2.841
sexmale       MI -1.73  0.2213   LD -3.694 0.548   full -3.087
age           MI -0.04  0.0083   LD -0.066 0.016   full -0.049
\end{Soutput}
\end{Schunk}
