csemTools: R Package for Estimating Conditional Standard Errors of Measurement for Test and Scale Scores

The R package csemTools provides a comprehensive implementation of classical procedures for estimating the conditional standard error of measurement (CSEM), a metric that has been underutilized in the validation of cognitive and non-cognitive scales based on dichotomous or ordinal responses. To support a robust and integrated workflow, csemTools offers a suite of functions that go beyond simple CSEM estimation. The package includes implementations of well-established methods from Feldt, Keats, Lord, Mollenkopf, and Thorndike. Building on the CSEM, it computes approximate conditional reliability via standardization, smooths CSEM curves to reduce local fluctuations, derives CSEMs for score groups defined by quantiles, and facilitates visual and quantitative comparisons across different CSEM procedures. Additionally, it provides an approximation for scale-score CSEM and a formal comparison of the global standard error of measurement against the entire CSEM curve. These features streamline the work of test developers and researchers, especially when reporting accuracy in non-educational or non-cognitive assessments. Ultimately, csemTools enables applied psychometricians to answer key questions about score precision: What is the CSEM for each score level? How do CSEM curves compare across methods? Is the global SEM representative of local precision? And what is the CSEM on the scale-score metric? By integrating these functionalities, the package fills a notable gap in the R ecosystem and promotes more nuanced and defensible interpretations of test scores.