IRTlike

IRTlike is a term used in psychometrics to describe models, methods, or approaches that resemble Item Response Theory (IRT) in their structure or aims. It is typically used informally to refer to models that estimate a latent ability from observed item responses and produce item response functions analogous to item characteristic curves. In IRTlike frameworks, individuals are characterized by a latent trait, and each item is described by parameters that govern difficulty and discrimination, with optional guessing or guessing-like parameters. These models can accommodate dichotomous or polytomous items and often rely on assumptions of local independence and unidimensional or multidimensional latent structure.

IRTlike models span a range of formal and informal approaches. They may include standard IRT families such as Rasch, 2PL, and 3PL, but also extensions or approximations that are not strictly classified as IRT, such as generalized linear models with an IRT-like link, or latent trait representations used in survey or diagnostic contexts. Estimation is typically via maximum likelihood or Bayesian methods, requiring careful specification and adequate sample size to obtain stable item and person parameters.

Applications include educational testing, certification, psychological assessment, and survey research, especially when item-level properties and latent ability estimates are of interest or when adaptive testing is employed. Limitations include potential model misspecification, the need for unidimensionality or explicit multidimensionality assumptions, and sensitivity to sample size. As a descriptor, IRTlike emphasizes resemblance to IRT rather than a fixed standard, and its precise meaning can vary by study.