Results 231 to 240 of about 2,604,808 (287)

Identifiability conditions in cognitive diagnosis: Implications for Q‐matrix estimation algorithms

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract The Q‐matrix of a cognitively diagnostic assessment (CDA), documenting the item‐attribute associations, is a key component of any CDA. However, the true Q‐matrix underlying a CDA is never known and must be estimated—typically by content experts.
Hyunjoo Kim, Hans Friedrich Köhn, Chia‐Yi Chiu   +2 more
wiley   +1 more source

Idiographic interrater reliability measures for intensive longitudinal multirater data

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Interrater reliability plays a crucial role in various areas of psychology. In this article, we propose a multilevel latent time series model for intensive longitudinal data with structurally different raters (e.g., self‐reports and partner reports).
Tobias Koch, Miriam F. Jaehne, Michaela Riediger, Antje Rauers, Jana Holtmann   +4 more
wiley   +1 more source

Power priors for latent variable mediation models under small sample sizes

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Latent variable models typically require large sample sizes for acceptable efficiency and reliable convergence. Appropriate informative priors are often required for gainfully employing Bayesian analysis with small samples. Power priors are informative priors built on historical data, weighted to account for non‐exchangeability with the ...
Lihan Chen, Milica Miočević, Carl F. Falk   +2 more
wiley   +1 more source

Bayesian inference for dynamic Q matrices and attribute trajectories in hidden Markov diagnostic classification models

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Hidden Markov diagnostic classification models capture how students' cognitive attributes evolve over time. This paper introduces a Bayesian Markov chain Monte Carlo algorithm for diagnostic classification models that jointly estimates time‐varying Q matrices, latent attributes, item parameters, attribute class proportions and transition ...
Chen‐Wei Liu
wiley   +1 more source

Latent Poisson count models for action count data from technology‐enhanced assessments

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Recent advances in computerized assessments have enabled the use of innovative item formats (e.g., drag‐and‐drop, scenario‐based), necessitating a flexible model that can capture systematic influence of item types on action counts. In this study, we present a refinement scheme that can explicitly model common features of items and allows ...
Gregory Arbet, Hyeon‐Ah Kang
wiley   +1 more source

Approximating multidimensionality with asymmetric unidimensional IRT models

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Unidimensional item response theory (IRT) models are widely used even in settings where assessment data exhibit subtle forms of multidimensionality. Recent empirical evidence suggests that when item difficulty is associated with dimensionality, asymmetric item characteristic curves (ICCs) emerge in the unidimensional approximation.
Xiangyi Liao, Yinqiu He, Daniel Bolt, James Soland, Carlin Conner, Emily J. Solari   +5 more
wiley   +1 more source

Composite marginal likelihood estimation of higher‐order diagnostic classification models under high dimensionality

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Although full‐information maximum likelihood (FIML) estimation is widely used for diagnostic classification models (DCMs), its computational efficiency deteriorates sharply in high‐dimensional settings. This scalability challenge is increasingly critical as DCMs are applied to large‐scale assessments, psychological testing and longitudinal ...
Minho Lee, Yon Soo Suh
wiley   +1 more source

New estimation methods for diagnostic classification models

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract This paper introduces a new class of estimators for cognitive diagnosis models (CDMs) based on the Cressie–Read family of ϕ$$ \phi $$‐divergences. Focusing on the loglinear CDM (LCDM), for which joint maximum likelihood estimation (JMLE) has been shown to be consistent, we propose a joint minimum divergence estimation (JMDE) framework.
Elena Castilla
wiley   +1 more source

Calibrating Bayesian inference

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information‐updating rules. In many applications, however, prior distributions are introduced merely as instruments to facilitate computation, rather than as representations of genuine subjective belief ...
Yang Liu, Jonathan P. Williams, Jan Hannig   +2 more
wiley   +1 more source