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_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.
