The package has been updated significantly in this verstion. In this version, I have:
o Updated ‘est_score’ function to estimate ability parameters much faster than the previous version of the function.
o Updated ‘est_irt’ and ‘est_item’ functions to estimate item parameters much faster than the previous version of the functions.
o Updated ‘test.info’ function to compute items infomation and test information much faster than the previous version of the function.
o Added an option to use a prior distribution of the item difficulty (or threshold) parameters in ‘est_irt’, ‘est_item’, and ‘llike_item’ functions.
o Solved unstable item parameter estimation of ‘est_irt’ and ‘est_item’ functions which occured when the scaling factor of ‘D’ is other than 1.0 and ‘use.aprior = TRUE’.
o Fixed an error which occured in the function ‘est_irt’ when the data set contains missing values and ‘fix.a.1pl = FALSE’.
o Included ‘summary’ method to summarize the IRT calibration results from ‘est_irt’ or ‘est_item’ objects.
o Included a new function of ‘getirt’ to extract various estimates results from ‘est_irt’ or ‘est_item’ objects.
o Fixed an error which happens when “DRM” is specified in the model name in the function ‘est_irt’.
o Included total computation time in the function ‘est_irt’.
o Changed the title of ‘irtplay’ package to “Unidimensional Item Response Theory Modeling”.
o Included a new function of ‘est_irt’ to fit unidimensional IRT models to mixture of dichotomous and polytomous item data using the marginal maximum likelihood estimation with expectation-maximization (MMLE-EM; Bock & Aitkin, 1981) algorithm.
o Included the fixed item parameter calibration (FIPC; Kim, 2006) approach, which is one of useful online calibration methods, in the function ‘est_irt’.
o Updated the documentation to explain how to implement the new function ‘est_irt’.
o Included well-known LSAT6 dichotomous response data set from Thissen (1982).
o Fixed a problem of inaccurate item parameter estimation in the function ‘est_item’ when a prior distribution of the slope parameter is used with a scaling factor other than D = 1.
o Updated the function ‘bring.flexmirt’ to read the item parameters of the generalized partial credit model when the number of score categories are two.
o Updated the function ‘est_score’ to find a smart starting value when MLE is used. More specifically, the smart starting value is a theta value where the log-likelihood is the maximum at the highest peak.
o Included the function ‘run_flexmirt’ to implement flexMIRT software (Cai, 2017) through R.
o Applied a prior distribution to the slope parameters of the IRT 1PL model when the slope parameters are constrained to be equal in the function of ‘est_item’.
o Fixed a problem of using staring values to estimate item parameters in the function of ‘est_item’.
o Fixed a non-convergence problem of the maximum likelihood estimation with fences (MLEF) in the function of ‘est_score’.
o Updated the description and introduction of the package.
o Updated the documentation to explain how to implement the function “est_item” in more detail.
o Updated the README.md file to explain how to implement the function “est_item” in more detail.
o Included the function ‘llike_score’ to compute the loglikelihood function of ability for an examinee.
o Updated the function ‘est_item’ to find better starting values for item parameter calibration.
o Updated the function ‘est_item’ to exclude items that contains no item response data during the item parameter estimation.
o Updated the function ‘est_item’ to count the number of item responses for each item used to estimate the item parameters.
o Updated the function ‘est_score’ to find better starting values when MLE is used.
o Updated the function ‘est_score’ to address NaNs of gradient values and NaNs of hessian values when MLE, MLEF, or MAP is used.
o Fixed a problem of the function ‘est_score’, which returned an error message when a vector of an examinee’s response data was used in the argument of ‘x’.
o Fixed a problem of the function ‘est_score’, which returned an error message when only one dichotomous item or one polytomous item was included in the item meta data set.
o Fixed a problem of the function ‘est_item’, which returned an error message when the inverse of hessian matrix is not obtainable.
o Included the ‘maximum likelihood estimation with fences scoring method (Han, 2016) in the function ’est_score’.
o Included the ‘inverse test characteristic curve (TCC)’ scoring method (e.g., Stocking, 1996) in the function ‘est_score’.
o Included the function ‘llike_item’ to compute the loglikelihood values of items.
o For the function ‘est_item’, default parameters of a-parameter prior distribution were revised
o Updated the function ‘est_item’ to find better starting values for item parameter calibration.
o Updated the function ‘est_score’ to estimate an ability in a brute force way when MLE or MAP fails to find the solution.
o Updated the function ‘irtfit’ to compute the likelihood ratio chi-square fit statistic (G2; Mckinley & Mills, 1985).
o initial release on CRAN