  Using a sample of 21 damped Lyman alpha systems (DLAs) and 35 sub-DLAs, we
evaluate the D-index = EW / Delta v x 1000 from high resolution spectra of the
MgII lambda 2796 profile. This sample represents an increase in sub-DLA D-index
statistics by a factor of four over the sample used by Ellison (2006). We
investigate various techniques to define the velocity spread (Delta v) of the
MgII line to determine an optimal D-index for the identification of DLAs. The
success rate of DLA identification is 50 -- 55%, depending on the velocity
limits used, improving by a few percent when the column density of FeII is
included in the D-index calculation. We recommend the set of parameters that is
judged to be most robust, have a combination of high DLA identification rate
(57%) and low DLA miss rate (6%) and most cleanly separate the DLAs and
sub-DLAs (Kolmogorov-Smirnov probability 0.5%). These statistics demonstrate
that the D-index is the most efficient technique for selecting low redshift DLA
candidates: 65% more efficient than selecting DLAs based on the equivalent
widths of MgII and FeII alone. We also investigate the effect of resolution on
determining the N(HI) of sub-DLAs. We convolve echelle spectra of sub-DLA Lya
profiles with Gaussians typical of the spectral resolution of instruments on
the Hubble Space Telescope and compare the best fit N(HI) values at both
resolutions. We find that the fitted HI column density is systematically
over-estimated by ~ 0.1 dex in the moderate resolution spectra compared to the
best fits to the original echelle spectra. This offset is due to blending of
nearby Lya clouds that are included in the damping wing fit at low resolution.
