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Mathematical, Statistical and Computing Psychology - RSS Feedhttp://psychsource.bps.org.ukPoint‐biserial correlation: Interval estimation, hypothesis testing, meta‐analysis, and sample size determination
http://psychsource.bps.org.uk/details/journalArticle/11187843/Pointbiserial-correlation-Interval-estimation-hypothesis-testing-metaanalysis-an.html
The point‐biserial correlation is a commonly used measure of effect size in two‐group designs. New estimators of point‐biserial correlation are derived from different forms of a standardized mean difference. Point‐biserial correlations are defined for designs with either fixed or random group sample sizes and can accommodate unequal variances. Confidence intervals and standard errors for the point‐biserial correlation estimators are derived from the sampling distributions for pooled‐variance...]]>2019-09-30T00:19:04ZMarginalized maximum a posteriori estimation for the four‐parameter logistic model under a mixture modelling framework
http://psychsource.bps.org.uk/details/journalArticle/11187292/Marginalized-maximum-a-posteriori-estimation-for-the-fourparameter-logistic-mode.html
The four‐parameter logistic model (4PLM) has recently attracted much interest in various applications. Motivated by recent studies that re‐express the four‐parameter model as a mixture model with two levels of latent variables, this paper develops a new expectation–maximization (EM) algorithm for marginalized maximum a posteriori estimation of the 4PLM parameters. The mixture modelling framework of the 4PLM not only makes the proposed EM algorithm easier to implement in practice, but also...]]>2019-09-25T00:00:00ZCombining diversity and dispersion criteria for anticlustering: A bicriterion approach
http://psychsource.bps.org.uk/details/journalArticle/11185107/Combining-diversity-and-dispersion-criteria-for-anticlustering-A-bicriterion-app.html
Most partitioning methods used in psychological research seek to produce homogeneous groups (i.e., groups with low intra‐group dissimilarity). However, there are also applications where the goal is to provide heterogeneous groups (i.e., groups with high intra‐group dissimilarity). Examples of these anticlustering contexts include construction of stimulus sets, formation of student groups, assignment of employees to project work teams, and assembly of test forms from a bank of items....]]>2019-09-12T02:30:04ZConfidence interval‐based sample size determination formulas and some mathematical properties for hierarchical data
http://psychsource.bps.org.uk/details/journalArticle/11183413/Confidence-intervalbased-sample-size-determination-formulas-and-some-mathematica.html
The use of hierarchical data (also called multilevel data or clustered data) is common in behavioural and psychological research when data of lower‐level units (e.g., students, clients, repeated measures) are nested within clusters or higher‐level units (e.g., classes, hospitals, individuals). Over the past 25 years we have seen great advances in methods for computing the sample sizes needed to obtain the desired statistical properties for such data in experimental evaluations. The present...]]>2019-09-07T11:25:15ZRevisiting dispersion in count data item response theory models: The Conway–Maxwell–Poisson counts model
http://psychsource.bps.org.uk/details/journalArticle/11178005/Revisiting-dispersion-in-count-data-item-response-theory-models-The-ConwayMaxwel.html
Count data naturally arise in several areas of cognitive ability testing, such as processing speed, memory, verbal fluency, and divergent thinking. Contemporary count data item response theory models, however, are not flexible enough, especially to account for over‐ and underdispersion at the same time. For example, the Rasch Poisson counts model (RPCM) assumes equidispersion (conditional mean and variance coincide) which is often violated in empirical data. This work introduces the...]]>2019-08-16T05:00:54ZA Latent Gaussian process model for analysing intensive longitudinal data
http://psychsource.bps.org.uk/details/journalArticle/11178006/A-Latent-Gaussian-process-model-for-analysing-intensive-longitudinal-data.html
Intensive longitudinal studies are becoming progressively more prevalent across many social science areas, and especially in psychology. New technologies such as smart‐phones, fitness trackers, and the Internet of Things make it much easier than in the past to collect data for intensive longitudinal studies, providing an opportunity to look deep into the underlying characteristics of individuals under a high temporal resolution. In this paper we introduce a new modelling framework for latent...]]>2019-08-16T05:00:36ZThe use of item scores and response times to detect examinees who may have benefited from item preknowledge
http://psychsource.bps.org.uk/details/journalArticle/11178007/The-use-of-item-scores-and-response-times-to-detect-examinees-who-may-have-benef.html
According to Wollack and Schoenig (2018, The Sage encyclopedia of educational research, measurement, and evaluation. Thousand Oaks, CA: Sage, 260), benefiting from item preknowledge is one of the three broad types of test fraud that occur in educational assessments. We use tools from constrained statistical inference to suggest a new statistic that is based on item scores and response times and can be used to detect examinees who may have benefited from item preknowledge for the case when the...]]>2019-08-16T04:59:22ZCombining mixture distribution and multidimensional IRTree models for the measurement of extreme response styles
http://psychsource.bps.org.uk/details/journalArticle/11175629/Combining-mixture-distribution-and-multidimensional-IRTree-models-for-the-measur.html
Personality constructs, attitudes and other non‐cognitive variables are often measured using rating or Likert‐type scales, which does not come without problems. Especially in low‐stakes assessments, respondents may produce biased responses due to response styles (RS) that reduce the validity and comparability of the measurement. Detecting and correcting RS is not always straightforward because not all respondents show RS and the ones who do may not do so to the same extent or in the same...]]>2019-08-06T03:34:59ZA mixture model for responses and response times with a higher‐order ability structure to detect rapid guessing behaviour
http://psychsource.bps.org.uk/details/journalArticle/11175628/A-mixture-model-for-responses-and-response-times-with-a-higherorder-ability-stru.html
Many educational and psychological assessments focus on multidimensional latent traits that often have a hierarchical structure to provide both overall‐level information and fine‐grained diagnostic information. A test will usually have either separate time limits for each subtest or an overall time limit for administrative convenience and test fairness. In order to complete the items within the allocated time, examinees frequently adopt different test‐taking behaviours during the test, such as...]]>2019-08-06T03:29:13ZThe counterintuitive impact of responses and response times on parameter estimates in the drift diffusion model
http://psychsource.bps.org.uk/details/journalArticle/11171413/The-counterintuitive-impact-of-responses-and-response-times-on-parameter-estimat.html
Given a drift diffusion model with unknown drift and boundary parameters, we analyse the behaviour of maximum likelihood estimates with respect to changes of responses and response times. It is shown analytically that a single fast response time can dominate the estimation in that no matter how many correct answers a test taker provides, the estimate of the drift (ability) parameter decreases to zero. In addition, it is shown that although higher drift rates imply shorter response times, the...]]>2019-07-21T23:38:40Z