Abstract
Checking the validity of test scores is important in both educational and psychological measurement. Person-fit analysis provides several statistics that help practitioners assessing whether individual item score vectors conform to a prespecified item response theory model or, alternatively, to a group of test takers. Software enabling easy access to most person-fit statistics was lacking up to now. The PerFit R package was written in order to fill in this void. A theoretical overview of relatively simple person-fit statistics is provided. A practical guide showing how the main functions of PerFit can be used is also given. Both numerical and graphical tools are described and illustrated using examples. The goal is to show how person-fit statistics can be easily applied to testing of questionnaire data.
Highlights
It is well known that total scores or estimated trait values do not always reflect the trait or proficiency level that a questionnaire or test intends to measure
In what follows we will focus on the person-fit statistics (PFSs) and related functions that are available in PerFit
We propose a graphical tool (function PRFplot()) that relies on observed item scores to better interpret person misfit, based on a nonparametric approach
Summary
It is well known that total scores or estimated trait values do not always reflect the trait or proficiency level that a questionnaire or test intends to measure. It is important to be able to detect whether test scores are invalid, that is, whether test scores are biased and not indicative of the true latent trait being measured. Several person-fit statistics (PFSs) have been proposed to detect inconsistent, aberrant, or misfitting patterns of item scores. Some researchers and practitioners find it difficult to implement personfit analyses in practice This might be explained by the mathematical complexity of (some of the) PFSs and by the lack of software that helps practitioners conducting this type of analysis. It is our hope that the R (R Core Team 2016) PerFit package (Tendeiro 2016) discussed in this paper can be helpful to a wide range of practitioners (see Meijer, Niessen, and Tendeiro 2016 and Tendeiro and Meijer 2014 for accessible person-fit overviews). We will summarize the main points of the paper and discuss further planned extensions for the package in the future
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