Jean‐Paul Fox
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View article: Redefining Item Response Models for Small Samples
Redefining Item Response Models for Small Samples Open
Popular item response theory (IRT) models are considered complex, mainly due to the inclusion of a random factor variable (latent variable). The random factor variable represents the incidental parameter problem since the number of paramet…
View article: Bayesian covariance structure modeling of interval-censored multi-way nested survival data
Bayesian covariance structure modeling of interval-censored multi-way nested survival data Open
A Bayesian covariance structure model (BCSM) is proposed for interval-censored multi-way nested survival data. This flexible modeling framework generalizes mixed effects survival models by allowing positive and negative associations among …
View article: R-package LNIRT for joint modeling of response accuracy and times
R-package LNIRT for joint modeling of response accuracy and times Open
In computer-based testing it has become standard to collect response accuracy (RA) and response times (RTs) for each test item. IRT models are used to measure a latent variable ( e.g ., ability, intelligence) using the RA observations. The…
View article: Bayesian Covariance Structure Modeling of Multi-Way Nested Data
Bayesian Covariance Structure Modeling of Multi-Way Nested Data Open
A Bayesian multivariate model with a structured covariance matrix for multi-way nested data is proposed. This flexible modeling framework allows for positive and for negative associations among clustered observations, and generalizes the w…
View article: Assessing an alternative for “negative variance components”: A gentle introduction to Bayesian covariance structure modeling for negative associations among patients with personalized treatments.
Assessing an alternative for “negative variance components”: A gentle introduction to Bayesian covariance structure modeling for negative associations among patients with personalized treatments. Open
The multilevel model (MLM) is the popular approach to describe dependences of hierarchically clustered observations. A main feature is the capability to estimate (cluster-specific) random effect parameters, while their distribution describ…
View article: Bayesian longitudinal item response modeling with multivariate asymmetric serial dependencies
Bayesian longitudinal item response modeling with multivariate asymmetric serial dependencies Open
It is usually impossible to impose experimental conditions in large-scale longitudinal (observational) studies in education. This increases the risk of bias due to for instance unobserved heterogeneity, missing background variables, and dr…
View article: LNIRT: An R Package for Joint Modeling of Response Accuracy and Times
LNIRT: An R Package for Joint Modeling of Response Accuracy and Times Open
In \textit{computer-based testing} it has become standard to collect response accuracy (RA) and response times (RTs) for each test item. IRT models are used to measure a latent variable (e.g., ability, intelligence) using the RA observatio…
View article: Generalized Linear Randomized Response Modeling using GLMMRR
Generalized Linear Randomized Response Modeling using GLMMRR Open
Randomized response (RR) designs are used to collect response data about sensitive behaviors (e.g., criminal behavior, sexual desires). The modeling of RR data is more complex, since it requires a description of the RR process. For the cla…
View article: Assessing an Alternative for `Negative Variance Components': A Gentle Introduction to Bayesian Covariance Structure Modelling for Negative Associations Among Patients with Personalized Treatments
Assessing an Alternative for `Negative Variance Components': A Gentle Introduction to Bayesian Covariance Structure Modelling for Negative Associations Among Patients with Personalized Treatments Open
The multilevel model (MLM) is the popular approach to describe dependences of hierarchically clustered observations. A main feature is the capability to estimate (cluster-specific) random effect parameters, while their distribution describ…
View article: <b>BFpack</b>: Flexible Bayes Factor Testing of Scientific Theories in <i>R</i>
<b>BFpack</b>: Flexible Bayes Factor Testing of Scientific Theories in <i>R</i> Open
There have been considerable methodological developments of Bayes factors for hypothesis testing in the social and behavioral sciences, and related fields. This development is due to the flexibility of the Bayes factor for testing multiple…
View article: Generalized Linear Randomized Response Modeling using GLMMRR
Generalized Linear Randomized Response Modeling using GLMMRR Open
Randomized response (RR) designs are used to collect response data about sensitive behaviors (e.g., criminal behavior, sexual desires). The modeling of RR data is more complex since it requires a description of the RR process. For the clas…
View article: The Bayesian Covariance Structure Model for Testlets
The Bayesian Covariance Structure Model for Testlets Open
Standard item response theory (IRT) models have been extended with testlet effects to account for the nesting of items; these are well known as (Bayesian) testlet models or random effect models for testlets. The testlet modeling framework …
View article: Bayesian covariance structure modelling for measurement invariance testing
Bayesian covariance structure modelling for measurement invariance testing Open
In a Bayesian Covariance Structure Model (BCSM) the dependence structure implied by random item parameters is modelled directly through the covariance structure. The corresponding measurement invariance assumption for an item is represente…
View article: BFpack: Flexible Bayes Factor Testing of Scientific Theories in R
BFpack: Flexible Bayes Factor Testing of Scientific Theories in R Open
There has been a tremendous methodological development of Bayes factors for hypothesis testing in the social and behavioral sciences, and related fields. This development is due to the flexibility of the Bayes factor for testing multiple h…
View article: Assessing and Validating Effects of a Data‐Based Decision‐Making Intervention on Student Growth for Mathematics and Spelling
Assessing and Validating Effects of a Data‐Based Decision‐Making Intervention on Student Growth for Mathematics and Spelling Open
Data‐based decision making (DBDM) is presumed to improve student performance in elementary schools in all subjects. The majority of studies in which DBDM effects have been evaluated have focused on mathematics. A hierarchical multiple sing…
View article: Bayesian Covariance Structure Modeling of Responses and Process Data
Bayesian Covariance Structure Modeling of Responses and Process Data Open
A novel Bayesian modeling framework for response accuracy (RA), response times (RTs) and other process data is proposed. In a Bayesian covariance structure modeling approach, nested and crossed dependences within test-taker data (e.g., wit…
View article: Understanding Therapeutic Change Process Research Through Multilevel Modeling and Text Mining
Understanding Therapeutic Change Process Research Through Multilevel Modeling and Text Mining Open
Online interventions hold great potential for Therapeutic Change Process Research (TCPR), a field that aims to relate in-therapeutic change processes to the outcomes of interventions. Online a client is treated essentially through the lang…
View article: Modeling Dependence Structures for Response Times in a Bayesian Framework
Modeling Dependence Structures for Response Times in a Bayesian Framework Open
A multivariate generalization of the log-normal model for response times is proposed within an innovative Bayesian modeling framework. A novel Bayesian Covariance Structure Model (BCSM) is proposed, where the inclusion of random-effect var…
View article: Invariance analyses in large-scale studies
Invariance analyses in large-scale studies Open
Large-scale surveys such as the Programme for International Student Assessment (PISA), the Teaching and Learning International Survey (TALIS), and the Programme for the International Assessment of Adult Competences (PIAAC) use advanced sta…
View article: Differential Item Functioning in PISA Due to Mode Effects
Differential Item Functioning in PISA Due to Mode Effects Open
One of the most important goals of the Programme for International Student Assessment (PISA) is assessing national changes in educational performance over time. These so-called trend results inform policy makers about the development of ab…
View article: Generalized Linear Mixed Models for Randomized Responses
Generalized Linear Mixed Models for Randomized Responses Open
Response bias (nonresponse and social desirability bias) is one of the main concerns when asking sensitive questions about behavior and attitudes. Self-reports on sensitive issues as in health research (e.g., drug and alcohol abuse), and s…
View article: Bayes Factor Testing of Multiple Intraclass Correlations
Bayes Factor Testing of Multiple Intraclass Correlations Open
The intraclass correlation plays a central role in modeling hierarchically structured data, such as educational data, panel data, or group-randomized trial data. It represents relevant information concerning the between-group and within-gr…
View article: Changes in Educational Leadership During A Data-Based Decision Making Intervention
Changes in Educational Leadership During A Data-Based Decision Making Intervention Open
School leaders are assumed to be important for the implementation of data-based decision making (DBDM), but little is known about changes in leadership during this implementation. Educational leadership was measured before, during, and aft…
View article: Multidimensional Assessment of Social Desirability Bias: An Application of Multiscale Item Randomized Response Theory to Measure Academic Misconduct
Multidimensional Assessment of Social Desirability Bias: An Application of Multiscale Item Randomized Response Theory to Measure Academic Misconduct Open
It is challenging for survey researchers to investigate sensitive topics due to concerns about socially desirable responding (SDR). The susceptibility to social desirability bias may vary not only between individuals (e.g., different perce…
View article: Bayesian Psychometric Scaling
Bayesian Psychometric Scaling Open
In educational and psychological studies, psychometric methods are involved in the measurement of constructs, and in constructing and validating measurement instruments. Assessment results are typically used to measure student proficiency …