Rockwood N. Efficient likelihood estimation of generalized structural equation models with a mix of normal and nonnormal responses. Psychometrika. 2021 Jun;86(2):642-67. doi: 10.1007/s11336-021-09770


A wide variety of one-parameter item response theory (IRT) models can now be easily run on SPSS using the SPIRIT macro. SPSS (IBM Corp., 2013) is an incredibly popular statistical software within the social sciences, yet does not currently have any built-in procedures that can run IRT analyses. The newly developed SPIRIT macro provides an accessible point-and-click interface that allows researchers to perform item response analyses on this established software. Users can run a large list of possible item response models, including one-parameter models with either a logit or probit link function, explanatory models with item and/or person covariates, models exploring differential item functioning (DIF), multidimensional models, multigroup models, linear logistic test models (LLTM) with item random effects, and rating scale models (for ordinal data). A benefit of this macro is its flexibility in being able to perform any reasonable combination of the aforementioned models to fit the user’s needs, while providing a convenient interface tailored to an IRT audience. This tool may be particularly useful in a pedagogical setting, where an instructor may wish to teach IRT at an introductory level but does not wish to burden new students with unfamiliar specialized IRT software. (PsycINFO Database Record (c) 2019 APA, all rights reserved)

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