The British Journal of Mathematical and Statistical Psychology 
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This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.Three new corrections for standardized person-fit statistics for tests with polytomous items
Br J Math Stat Psychol. 2024 Apr 17. doi: 10.1111/bmsp.12342. Online ahead of print.ABSTRACTRecent years have seen a growing interest in the development of person-fit statistics for tests with polytomous items. Some of the most popular person-fit statistics for such tests belong to the class of standardized person-fit statistics, T $$ T $$ , that is assumed to have a standard normal null distribution. However, this distribution only holds when (a) the true ability parameter is known and (b) an infinite number of items are available. In practice, both conditions are violated, and the quality of person-fit results is expec...
Source: The British Journal of Mathematical and Statistical Psychology - April 18, 2024 Category: Statistics Authors: Kylie Gorney Source Type: research
Modelling motion energy in psychotherapy: A dynamical systems approach
In this study we introduce an innovative mathematical and statistical framework for the analysis of motion energy dynamics in psychotherapy sessions. Our method combines motion energy dynamics with coupled linear ordinary differential equations and a measurement error model, contributing new clinical parameters to enhance psychotherapy research. Our approach transforms raw motion energy data into an interpretable account of therapist-patient interactions, providing novel insights into the dynamics of these interactions. A key aspect of our framework is the development of a new measure of synchrony between the motion energi...
Source: The British Journal of Mathematical and Statistical Psychology - April 17, 2024 Category: Statistics Authors: Itai Dattner Source Type: research
Modelling motion energy in psychotherapy: A dynamical systems approach
In this study we introduce an innovative mathematical and statistical framework for the analysis of motion energy dynamics in psychotherapy sessions. Our method combines motion energy dynamics with coupled linear ordinary differential equations and a measurement error model, contributing new clinical parameters to enhance psychotherapy research. Our approach transforms raw motion energy data into an interpretable account of therapist-patient interactions, providing novel insights into the dynamics of these interactions. A key aspect of our framework is the development of a new measure of synchrony between the motion energi...
Source: The British Journal of Mathematical and Statistical Psychology - April 17, 2024 Category: Statistics Authors: Itai Dattner Source Type: research
Assessing quality of selection procedures: Lower bound of false positive rate as a function of inter-rater reliability
Br J Math Stat Psychol. 2024 Apr 15. doi: 10.1111/bmsp.12343. Online ahead of print.ABSTRACTInter-rater reliability (IRR) is one of the commonly used tools for assessing the quality of ratings from multiple raters. However, applicant selection procedures based on ratings from multiple raters usually result in a binary outcome; the applicant is either selected or not. This final outcome is not considered in IRR, which instead focuses on the ratings of the individual subjects or objects. We outline the connection between the ratings' measurement model (used for IRR) and a binary classification framework. We develop a simple ...
Source: The British Journal of Mathematical and Statistical Psychology - April 16, 2024 Category: Statistics Authors: Franti šek Bartoš Patr ícia Martinková Source Type: research
The effective sample size in Bayesian information criterion for level-specific fixed and random-effect selection in a two-level nested model
In this study, we derive the BIC's penalty term for level-specific fixed- and random-effect selection in a two-level nested design. In this new version of BIC, called BIC E 1 , this penalty term is decomposed into two parts if the random-effect variance-covariance matrix has full rank: (a) a term with the log of average sample size per cluster and (b) the total number of parameters times the log of the total number of clusters. Furthermore, we derive the new version of BIC, called BIC E 2 , in the presence of redundant random effects. We show that the derived formulae, BIC E 1 and BIC E 2 , adhere t...
Source: The British Journal of Mathematical and Statistical Psychology - April 9, 2024 Category: Statistics Authors: Sun-Joo Cho Hao Wu Matthew Naveiras Source Type: research
The effective sample size in Bayesian information criterion for level-specific fixed and random-effect selection in a two-level nested model
In this study, we derive the BIC's penalty term for level-specific fixed- and random-effect selection in a two-level nested design. In this new version of BIC, called BIC E 1 , this penalty term is decomposed into two parts if the random-effect variance-covariance matrix has full rank: (a) a term with the log of average sample size per cluster and (b) the total number of parameters times the log of the total number of clusters. Furthermore, we derive the new version of BIC, called BIC E 2 , in the presence of redundant random effects. We show that the derived formulae, BIC E 1 and BIC E 2 , adhere t...
Source: The British Journal of Mathematical and Statistical Psychology - April 9, 2024 Category: Statistics Authors: Sun-Joo Cho Hao Wu Matthew Naveiras Source Type: research
The effective sample size in Bayesian information criterion for level-specific fixed and random-effect selection in a two-level nested model
In this study, we derive the BIC's penalty term for level-specific fixed- and random-effect selection in a two-level nested design. In this new version of BIC, called BIC E 1 , this penalty term is decomposed into two parts if the random-effect variance-covariance matrix has full rank: (a) a term with the log of average sample size per cluster and (b) the total number of parameters times the log of the total number of clusters. Furthermore, we derive the new version of BIC, called BIC E 2 , in the presence of redundant random effects. We show that the derived formulae, BIC E 1 and BIC E 2 , adhere t...
Source: The British Journal of Mathematical and Statistical Psychology - April 9, 2024 Category: Statistics Authors: Sun-Joo Cho Hao Wu Matthew Naveiras Source Type: research
The effective sample size in Bayesian information criterion for level-specific fixed and random-effect selection in a two-level nested model
In this study, we derive the BIC's penalty term for level-specific fixed- and random-effect selection in a two-level nested design. In this new version of BIC, called BIC E 1 , this penalty term is decomposed into two parts if the random-effect variance-covariance matrix has full rank: (a) a term with the log of average sample size per cluster and (b) the total number of parameters times the log of the total number of clusters. Furthermore, we derive the new version of BIC, called BIC E 2 , in the presence of redundant random effects. We show that the derived formulae, BIC E 1 and BIC E 2 , adhere t...
Source: The British Journal of Mathematical and Statistical Psychology - April 9, 2024 Category: Statistics Authors: Sun-Joo Cho Hao Wu Matthew Naveiras Source Type: research
The effective sample size in Bayesian information criterion for level-specific fixed and random-effect selection in a two-level nested model
In this study, we derive the BIC's penalty term for level-specific fixed- and random-effect selection in a two-level nested design. In this new version of BIC, called BIC E 1 , this penalty term is decomposed into two parts if the random-effect variance-covariance matrix has full rank: (a) a term with the log of average sample size per cluster and (b) the total number of parameters times the log of the total number of clusters. Furthermore, we derive the new version of BIC, called BIC E 2 , in the presence of redundant random effects. We show that the derived formulae, BIC E 1 and BIC E 2 , adhere t...
Source: The British Journal of Mathematical and Statistical Psychology - April 9, 2024 Category: Statistics Authors: Sun-Joo Cho Hao Wu Matthew Naveiras Source Type: research
A two-step item bank calibration strategy based on 1-bit matrix completion for small-scale computerized adaptive testing
This study addresses these challenges by developing a two-step item bank calibration strategy that leverages the 1-bit matrix completion method in conjunction with two distinct incomplete pretesting designs. We introduce two novel 1-bit matrix completion-based imputation methods specifically designed to tackle the issues associated with item calibration in the presence of sparse response data and limited sample sizes. To demonstrate the effectiveness of these approaches, we conduct a comparative assessment against several established item parameter estimation methods capable of handling missing data. This evaluation is car...
Source: The British Journal of Mathematical and Statistical Psychology - April 5, 2024 Category: Statistics Authors: Yawei Shen Shiyu Wang Houping Xiao Source Type: research
A comparison of different measures of the proportion of explained variance in multiply imputed data sets
Br J Math Stat Psychol. 2024 Apr 5. doi: 10.1111/bmsp.12344. Online ahead of print.ABSTRACTThe proportion of explained variance is an important statistic in multiple regression for determining how well the outcome variable is predicted by the predictors. Earlier research on 20 different estimators for the proportion of explained variance, including the exact Olkin-Pratt estimator and the Ezekiel estimator, showed that the exact Olkin-Pratt estimator produced unbiased estimates, and was recommended as a default estimator. In the current study, the same 20 estimators were studied in incomplete data, with missing data being t...
Source: The British Journal of Mathematical and Statistical Psychology - April 5, 2024 Category: Statistics Authors: Joost R van Ginkel Julian D Karch Source Type: research
A two-step item bank calibration strategy based on 1-bit matrix completion for small-scale computerized adaptive testing
This study addresses these challenges by developing a two-step item bank calibration strategy that leverages the 1-bit matrix completion method in conjunction with two distinct incomplete pretesting designs. We introduce two novel 1-bit matrix completion-based imputation methods specifically designed to tackle the issues associated with item calibration in the presence of sparse response data and limited sample sizes. To demonstrate the effectiveness of these approaches, we conduct a comparative assessment against several established item parameter estimation methods capable of handling missing data. This evaluation is car...
Source: The British Journal of Mathematical and Statistical Psychology - April 5, 2024 Category: Statistics Authors: Yawei Shen Shiyu Wang Houping Xiao Source Type: research
A comparison of different measures of the proportion of explained variance in multiply imputed data sets
Br J Math Stat Psychol. 2024 Apr 5. doi: 10.1111/bmsp.12344. Online ahead of print.ABSTRACTThe proportion of explained variance is an important statistic in multiple regression for determining how well the outcome variable is predicted by the predictors. Earlier research on 20 different estimators for the proportion of explained variance, including the exact Olkin-Pratt estimator and the Ezekiel estimator, showed that the exact Olkin-Pratt estimator produced unbiased estimates, and was recommended as a default estimator. In the current study, the same 20 estimators were studied in incomplete data, with missing data being t...
Source: The British Journal of Mathematical and Statistical Psychology - April 5, 2024 Category: Statistics Authors: Joost R van Ginkel Julian D Karch Source Type: research
A two-step item bank calibration strategy based on 1-bit matrix completion for small-scale computerized adaptive testing
This study addresses these challenges by developing a two-step item bank calibration strategy that leverages the 1-bit matrix completion method in conjunction with two distinct incomplete pretesting designs. We introduce two novel 1-bit matrix completion-based imputation methods specifically designed to tackle the issues associated with item calibration in the presence of sparse response data and limited sample sizes. To demonstrate the effectiveness of these approaches, we conduct a comparative assessment against several established item parameter estimation methods capable of handling missing data. This evaluation is car...
Source: The British Journal of Mathematical and Statistical Psychology - April 5, 2024 Category: Statistics Authors: Yawei Shen Shiyu Wang Houping Xiao Source Type: research
A comparison of different measures of the proportion of explained variance in multiply imputed data sets
Br J Math Stat Psychol. 2024 Apr 5. doi: 10.1111/bmsp.12344. Online ahead of print.ABSTRACTThe proportion of explained variance is an important statistic in multiple regression for determining how well the outcome variable is predicted by the predictors. Earlier research on 20 different estimators for the proportion of explained variance, including the exact Olkin-Pratt estimator and the Ezekiel estimator, showed that the exact Olkin-Pratt estimator produced unbiased estimates, and was recommended as a default estimator. In the current study, the same 20 estimators were studied in incomplete data, with missing data being t...
Source: The British Journal of Mathematical and Statistical Psychology - April 5, 2024 Category: Statistics Authors: Joost R van Ginkel Julian D Karch Source Type: research
