libirt libirt is a set of functions written in C to estimate the items and abilities from the responses of subjects to a questionnaire.
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theory response Item C functions theory library questionnaire estimation

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libirt is a set of functions written in C to estimate the items and abilities from the responses of subjects to a questionnaire. The Item Response Theory Library (libirt) is a set of functions written in C to estimate the items and abilities from the responses of subjects to a questionnaire.While two command line programs ("irt" and "mirt") are also provided, the library is mostly being used in others applications.MODELS1PLM - One parameter logistic model. The threshold (difficulty or location parameter) of each item is estimated while the slope (discrimination or scale parameter) of each item can be fixed. 2PLM - Two parameters logistic model. Both the threshold and slope of each item are estimated. 3PLM - Three parameters logistic model. The threshold, slope and asymptote (guessing parameter) are estimated. Nominal response model - The threshold and slope of each option are estimated. Graded model - The modal threshold of each option and the slope of each item are estimated. Nonparametric - In addition to the parametric models, libirt can estimate the response functions by smoothing (see the methods section). METHODSThe parametric estimators are: MMLE - Marginal Maximum Likelihood Estimator.BME - Bayes Modal Estimator.The nonparametric estimators are: Kernel smoothing - The Nadaraya-Watson regression used in TestGraf.PMMLE - Penalized Marginal Maximum Likelihood Estimator.The abilities estimators are: EAP - Expected A Posteriori.ML - Maximum Likelihood (for the univariate logistic models only).

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