Information Analysis for Test and Rating Scale Data

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Documentation for package ‘TestGardener’ version 3.3.5

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Analyze Analyze test or rating scale data defined in 'dataList'.
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
DFfun Compute the first and second derivatives of the negative log likelihoods
entropies Entropy measures of inter-item dependency
Entropy_plot Plot item entropy curves for selected items or questions.
eval.surp Values of a Functional Data Object Defining Surprisal Curves.
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.
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
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.
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.
Sensitivity_plot Plots all the sensitivity curves for selected items or questions.
SimulateData Simulate Choice Data from a Previous Analysis
smooth.ICC Smooth binned probability and surprisal values to make an 'ICC' object.
smooth.surp Fit data with surprisal smoothing.
Spca Functional principal components analysis of information curve
Spca_plot Plot the test information or scale curve in either two or three dimensions.
surp.fit Objects resulting for assessing fit of surprisal matrix to surprisal data
TestGardener Analyses of Tests and Rating Scales using Information or Surprisal
TestInfo_svd Image of the Test Tnformation Curve in 2 or 3 Dimensions
TG_analysis Statistics for Multiple choice Tests, Rating Scales and Other Choice Data)
TG_density.fd Compute a Probability Density Function