CHANGES IN OPTMATCH VERSION 0.6-1
NEW FEATURES
* New mdist method to extract propensity scores from models fitted using bigglm in package "biglm".
* mdist's formula method now understands grouping factors indicated with a pipe ("|")
* informative error message for mdist called on numeric vectors
* updated mdist documentation
CHANGES IN OPTMATCH VERSION 0.6

NEW FEATURES
* There is a new generic function, mdist(), for creating matching distances.  It accepts: fitted glm's, which it uses to extract propensity distances; formulas, which it uses to construct squared Mahalanobis distances; and functions, with which a user can construct his or her own type of distance.  The function method is more intuitive to work with than the older makedist() function.  
* A new function, caliper(), builds on the mdist() structure to provide a convenient way to add calipers to a distance.  In contrast to earlier ways of adding calipers, caliper() has an optional argument specify observations to be excluded from the caliper requirement --- this permits one to relax it for just a few observations, for instance.
* summary.optmatch() now removes strata in which matching failed (b/c the matching problem was found to be infeasible) before summarizing.  It also indicates when such strata are present, and how many observations fall in them.
* Demo has been updated to reflect changes as of version 0.4, 0.5, 0.6.

DEPRECATED & DEFUNCT
* The vignette is sufficiently out of date that it's been removed.  

BUG FIXES
* subsetting of objects of class optmatch now preserves matched.distances attribute.
* fixed bug in maxControlsCap/minControlsCap whereby they behaved unreliably on subclasses within which some subjects had no permissible matches.  
* Removed unnecessary panic in fullmatch when it was given a min.controls argument with attributes other than names (as when it is created by tapply()).
* fixed bug wherein summary.optmatch fails to retrieve balance tests if given a propensity model that had function calls in its formula.
* Documentation pages for fullmatch, pairmatch filled out a bit.

Changes in optmatch version 0.5
New features:
* summary.optmatch() completely revised.  It now reports information about
the configuration of the matched sets and about matched distances.  In 
addition, if given a fitted propensity model as a second argument it 
summarizes covariate balance.
