Changes in version: ltm_0.4-0

  o "grm()" function is introduced for fitting Graded Response models under IRT.

  o "plot()" function has a new argument, 'type', that indicates whether Item Characteristic Curves or
    Item Information Curves should be plotted. If 'items = 0', the Test Information Curve is plotted. 
    Some extra arguments have been also introduced, like 'lty' and 'col'.

  o Both "grm()" and "rasch()" report parameter estimates under the IRT parameterization, by default. "ltm()" does the
    same for the two parameter logistic model.

  o "margins()" is now a generic function with methods for 'grm', 'ltm' and 'rasch' objects.

  o "factor.scores()" has a new argument 'resp.patterns' that provides specific response patterns for which
    factor scores should be computed. "factor.scores.ltm()" has now as default method 'EB' instead of 'Component'.

  o "grm()" does not use random starting values unless 'start.val = "random"'; look at the help file for more info.
    
  o "descript()" can now also handle data sets with polytomous responses.

  o the function "mult.choice()" has been introduced that can convert multiple choice responses to 0-1 data; this
    can be used in "ltm()" and "rasch()".

  o the function "information()" has been introduced that computes the area under the test information curve.

  o the demo for "rasch()" has been updated.

  o corrected some typos in .Rd files.


==============================

Changes in version: ltm_0.3-1

  o "coef.rasch()" and "coef.ltm()" now obey to the 'IRT.param' argument.

  o standard errors are now reported also for the case where the dicriminitation parameters are fixed.

  o a demo for "rasch()" has been added.


==============================

Changes in version: ltm_0.3-0

  o a new logical argument -- 'IRT.param' (default to FALSE) -- has been introduced in both "ltm()" and "rasch()"
    which if TRUE reports the coefficients under the usual IRT parameterization.

  o "plot.ltm()" and "plot.rasch()" improved: (i) if the column names of the input data are not NULL then they are 
    used to denote the items, (ii) printing of legend is now optional -- see argument 'legend', (iii) if 'legend = FALSE',
    'text()' is used to add as labels to the existing plot either the column names of the input data or numbers denoting
    the items, (iv) there is an argument 'items' controlling which items are plotted.

  o 'constraint' argument in "ltm()" accepts now more general fixed value constraints. For more info check 
    help("ltm", package = "ltm").

  o a "fitted()" method has been introduced for both classes 'ltm' and 'rasch'.

  o a "logLik()" method has been introduced for both classes 'ltm' and 'rasch'.

  o a "vcov()" method has been introduced for both classes 'ltm' and 'rasch'.

  o now robust standard errors estimation is done inside "vcov.rasch()" and "vcov.ltm()".

  o "coef.ltm()" and "coef.rasch" have a new logical argument 'prob' which if TRUE, then the probabilities
    of a positive response for the median individual are returned.

  o "descript()" now has a print method -- 'print' argument no longer available.


==============================

Changes in version: ltm_0.2-1

  o "rasch()" now contains an extra argument 'constraint' that permits incorporation of fixed-value constraints. 
    For more info check help("rasch", package = "ltm").

  o "anova.rasch()" now also performs LRTs between constrained and unconstrained Rasch models.
  
  o a "vcov()" method has been introduced for "rasch()" objects.

  o Edited *.Rd files to use \method{} for generics.

  o corrected some typos in .Rd files.

