Analyze                 Analyze test or rating scale data defined in
                        'dataList'.
DFfun                   Compute the first and second derivatives of the
                        negative log likelihoods
Entropy_plot            Plot item entropy curves for selected items or
                        questions.
Fcurve                  Construct grid of 101 values of the fitting
                        function
Ffun                    Compute the negative log likelihoods associated
                        with a vector of score index values.
Ffuns_plot              Plot a selection of fit criterion F functions
                        and their first two derivatives.
ICC                     Plotting probability and surprisal curves for
                        an item
ICC_plot                Plot probability and surprisal curves for test
                        or scale items.
Power_plot              Plot item power curves for selected items or
                        questions.
Quant_13B_problem_chcemat
                        Test data for 24 math calculation questions
                        from the SweSAT data.
Quant_13B_problem_dataList
                        List of objects essential for an analysis of
                        the abbreviated SweSAT Quantitative multiple
                        choice test.
Quant_13B_problem_infoList
                        Arclength or information parameter list for 24
                        items from the quantitative SweSAT subtest.
Quant_13B_problem_key   Option information for the short form of the
                        SweSAT Quantitative test.
Quant_13B_problem_parmList
                        Parameter list for 24 items from the
                        quantitative SweSAT subtest.
Sbinsmth                Estimate the option probability and surprisal
                        curves.
Sbinsmth.init           Initialize surprisal smoothing of choice data.
Sbinsmth_nom            List vector containing numbers of options and
                        boundaries.
Scope_plot              Plot the score index 'index' as a function of
                        arc length.
Sensitivity_plot        Plots all the sensitivity curves for selected
                        items or questions.
SimulateData            Simulate Choice Data from a Previous Analysis
Spca                    Functional principal components analysis of
                        information curve
Spca_plot               Plot the test information or scale curve in
                        either two or three dimensions.
TG_analysis             Statistics for Multiple choice Tests, Rating
                        Scales and Other Choice Data)
TG_density.fd           Compute a Probability Density Function
TestGardener            Analyses of Tests and Rating Scales using
                        Information or Surprisal
TestInfo_svd            Image of the Test Tnformation Curve in 2 or 3
                        Dimensions
chcemat_simulate        Simulate a test or scale data matrix.
dataSimulation          Simulation Based Estimates of Error Variation
                        of Score Index Estimates
density_plot            Plot the probability density function for a set
                        of test scores
entropies               Entropy measures of inter-item dependency
eval.surp               Values of a Functional Data Object Defining
                        Surprisal Curves.
index2info              Compute results using arc length or information
                        as the abscissa.
index_distn             Compute score density
index_fun               Compute optimal scores
index_search            Ensure that estimated score index is global
make_dataList           Make a list object containing information
                        required for analysis of choice data.
mu                      Compute the expected test score by substituting
                        probability of choices for indicator variable
                        0-1 values. Binary items assumed coded as two
                        choice items.
mu_plot                 Plot expected test score as a function of score
                        index
scoreDensity            Compute and plot a score density histogram and
                        and curve.
scorePerformance        Calculate mean squared error and bias for a set
                        of score index values from simulated data.
smooth.ICC              Smooth binned probability and surprisal values
                        to make an 'ICC' object.
smooth.surp             Fit data with surprisal smoothing.
surp.fit                Objects resulting for assessing fit of
                        surprisal matrix to surprisal data
