Changes in version: ltm_0.7-1

  o a bug was fixed in "grm()".

  o the "plot()" method for all IRT models has an extra logical argument 'plot' that controls whether the plot will
    be produced or not. If 'plot = FALSE', then the values used to create the plot are returned.

  o the "plot()" methods for 'descript' objects has an extra argument 'items' specifying which items to plot.

  o a better "print()" method for 'rcor.test' objects has been added.

  o package 'gtools' is no longer required.


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

Changes in version: ltm_0.7-0

  o function "biserial.cor()" has been included that computes the point biserial correlation between a dichotomous and 
    a continuous variable.

  o in the "plot()" method for 'grm' objects, the option for Operation Characteristic Curves has been added.

  o "rmvlogis()" has a new argument 'IRT' specifying whether the parameters are under the IRT parameterization.

  o "rmvlogis()" has extra available distributions for the latent variable.

  o a "plot()" method has been added for 'descript' objects, producing the plot of Total Score versus Proportion of 
    Correct for each item.


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

Changes in version: ltm_0.6-1

  o starting values for "ltm()" are now by default deterministic; for random starting values you may use 
    'start.val = "random"'.

  o "anova.rasch()" now only computes likelihood ratio test between nested models. The parametric Bootstrap 
    goodness-of-fit test in now implemented in function "GoF.rasch()".

  o "information()" returns now a list of class 'information' for which a "print()" method has been added.

  o 'Lsat' and 'Wirs' data.frames have been renamed to 'LSAT' and 'WIRS', respectively.

  o "rmvlogis()" has an extra argument 'link' that specifies the link function.

  o additions and corrections in Rd files.


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

Changes in version: ltm_0.6-0

  o "tpm()" function is introduced for fitting Birnbaum's Three Parameter model.

  o "grm()" modified to handle dichotmous items as well.

  o "rmvlogis()" function can be used to simulate binary variates under dichotomous IRT models.

  o "descript()" returns more output.

  o the "plot()" method for classes 'grm', 'ltm', 'rasch', and 'tpm' contains the new argument 'z' that
    specifies the latent variable values used in the plots.

  o a bug was fixed in "coef.rasch()" and "coef.ltm()".

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


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

Changes in version: ltm_0.5-1

  o the Gauss-Hermite rule has been upgraded; functions "grm()", "ltm()" and "rasch()" may produce slightly different 
    parameter estimates from the previous versions.

  o some issues regarding missing values and singular designs have been resolved in "start.val.rasch()".

  o a bug was fixed in "coef.grm()".


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

Changes in version: ltm_0.5-0

  o the "plot()" method for 'grm', 'ltm' and 'rasch' objects is now more flexible containing a number of extra arguments.

  o starting values for "rasch()" are now by default deterministic; for random starting values you may use 
    'start.val = "random"'.

  o the "coef()" method for 'ltm' and 'rasch' objects has an extra argument 'order' that sorts the coefficients according
    to the difficulty parameters.

  o corrected some typos in .Rd files.


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

Changes in version: ltm_0.4-1

  o "information()" now has the argument 'items' that specifies for which items the information should be computed in
    the specified interval. By default, the test information is computed.

  o a bug was fixed in "print.grm()".

  o a bug was fixed in "plot.grm()".


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

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 "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 function "rcor.test()" has been introduced that computes and tests for the significance of sample correlation
    coefficients.

  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.

