645 results match your criteria British Journal of Mathematical and Statistical Psychology [Journal]


An exploratory analysis of the latent structure of process data via action sequence autoencoders.

Br J Math Stat Psychol 2020 May 22. Epub 2020 May 22.

Department of Statistics, Columbia University, New York, New York, USA.

Computer simulations have become a popular tool for assessing complex skills such as problem-solving. Log files of computer-based items record the human-computer interactive processes for each respondent in full. The response processes are very diverse, noisy, and of non-standard formats. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12203DOI Listing

D-optimal design for the Rasch counts model with multiple binary predictors.

Br J Math Stat Psychol 2020 May 14. Epub 2020 May 14.

Institute of Mathematical Stochastics, University of Magdeburg, Germany.

In this paper we derive optimal designs for the Rasch Poisson counts model and its extended version of the (generalized) negative binomial counts model incorporating several binary predictors for the difficulty parameter. To efficiently estimate the regression coefficients of the predictors, locally D-optimal designs are developed. After an introduction to the Rasch Poisson counts model and its extension, we will specify these models as particular generalized linear models. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12204DOI Listing

Inferences about which of J dependent groups has the largest robust measure of location.

Authors:
Rand R Wilcox

Br J Math Stat Psychol 2020 May 5. Epub 2020 May 5.

Department of Psychology, University of Southern California, Los Angeles, California, USA.

Recently, a multiple comparisons procedure was derived with the goal of determining whether it is reasonable to make a decision about which of J independent groups has the largest robust measure of location. This was done by testing hypotheses aimed at comparing the group with the largest estimate to the remaining J - 1 groups. It was demonstrated that for the goal of controlling the familywise error rate, meaning the probability of one or more Type I errors, well-known improvements on the Bonferroni method can perform poorly. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12205DOI Listing

Stopping rules for multi-category computerized classification testing.

Br J Math Stat Psychol 2020 Apr 2. Epub 2020 Apr 2.

University of Notre Dame, Notre Dame, Indiana, USA.

Computerized classification testing (CCT) aims to classify persons into one of two or more possible categories to make decisions such as mastery/non-mastery or meet most/meet all/exceed. A defining feature of CCT is its stopping criterion: the test terminates when there is enough confidence to make a decision. There is abundant research on CCT with a single cut-off, and two common stopping criteria are the sequential probability ratio test (SPRT) statistic and the generalized likelihood ratio statistic (GLR). Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12202DOI Listing

Curiosity-driven recommendation strategy for adaptive learning via deep reinforcement learning.

Br J Math Stat Psychol 2020 Feb 21. Epub 2020 Feb 21.

Department of Mathematics, Hong Kong University of Science and Technology, Kowloon, Hong Kong.

The design of recommendation strategies in the adaptive learning systems focuses on utilizing currently available information to provide learners with individual-specific learning instructions. As a critical motivate for human behaviours, curiosity is essentially the drive to explore knowledge and seek information. In a psychologically inspired view, we propose a curiosity-driven recommendation policy within the reinforcement learning framework, allowing for an efficient and enjoyable personalized learning path. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12199DOI Listing
February 2020

Can we disregard the whole model? Omnibus non-inferiority testing for R in multi-variable linear regression and in ANOVA.

Br J Math Stat Psychol 2020 Feb 13. Epub 2020 Feb 13.

Eindhoven University of Technology, The Netherlands.

Determining a lack of association between an outcome variable and a number of different explanatory variables is frequently necessary in order to disregard a proposed model (i.e., to confirm the lack of a meaningful association between an outcome and predictors). Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12201DOI Listing
February 2020

A new quantile estimator with weights based on a subsampling approach.

Br J Math Stat Psychol 2020 Jan 16. Epub 2020 Jan 16.

Department of Statistics, Faculty of Sciences, Dokuz Eylül University, İzmir, Turkey.

Quantiles are widely used in both theoretical and applied statistics, and it is important to be able to deploy appropriate quantile estimators. To improve performance in the lower and upper quantiles, especially with small sample sizes, a new quantile estimator is introduced which is a weighted average of all order statistics. The new estimator, denoted NO, has desirable asymptotic properties. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12198DOI Listing
January 2020

Modelling monotonic effects of ordinal predictors in Bayesian regression models.

Br J Math Stat Psychol 2020 Jan 13. Epub 2020 Jan 13.

Assistance publique - Hôpitaux de Paris, France.

Ordinal predictors are commonly used in regression models. They are often incorrectly treated as either nominal or metric, thus under- or overestimating the information contained. Such practices may lead to worse inference and predictions compared to methods which are specifically designed for this purpose. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12195DOI Listing
January 2020

A latent topic model with Markov transition for process data.

Br J Math Stat Psychol 2020 Jan 8. Epub 2020 Jan 8.

Columbia University, New York, New York, USA.

We propose a latent topic model with a Markov transition for process data, which consists of time-stamped events recorded in a log file. Such data are becoming more widely available in computer-based educational assessment with complex problem-solving items. The proposed model can be viewed as an extension of the hierarchical Bayesian topic model with a hidden Markov structure to accommodate the underlying evolution of an examinee's latent state. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12197DOI Listing
January 2020

Modelling inter-individual differences in latent within-person variation: The confirmatory factor level variability model.

Authors:
Steffen Nestler

Br J Math Stat Psychol 2020 Jan 8. Epub 2020 Jan 8.

University of Münster, Germany.

Psychological theories often produce hypotheses that pertain to individual differences in within-person variability. To empirically test the predictions entailed by such hypotheses with longitudinal data, researchers often use multilevel approaches that allow them to model between-person differences in the mean level of a certain variable and the residual within-person variance. Currently, these approaches can be applied only when the data stem from a single variable. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12196DOI Listing
January 2020

The danger of conflating level-specific effects of control variables when primary interest lies in level-2 effects.

Br J Math Stat Psychol 2019 Dec 19. Epub 2019 Dec 19.

Vanderbilt University, Nashville, Tennessee, USA.

In the multilevel modelling literature, methodologists widely acknowledge that a level-1 variable can have distinct within-cluster and between-cluster effects, and that failing to disaggregate these can yield a slope estimate that is an uninterpretable, conflated blend of the two. Methodologists have stated, however, that including conflated slopes of level-1 variables in a model is not problematic if substantive interest lies only in effects of level-2 predictors. Researchers commonly follow this advice and use methods that do not disaggregate effects of level-1 control variables (e. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12194DOI Listing
December 2019

Data-driven Q-matrix validation using a residual-based statistic in cognitive diagnostic assessment.

Br J Math Stat Psychol 2019 Nov 25. Epub 2019 Nov 25.

Department of Psychology, University of Notre Dame, Notre Dame, Indiana, USA.

In a cognitive diagnostic assessment (CDA), attributes refer to fine-grained knowledge points or skills. The Q-matrix is a central component of CDA, which specifies the relationship between items and attributes. Oftentimes, attributes and Q-matrix are defined by subject-matter experts, and assumed to be appropriate without any misspecifications. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12191DOI Listing
November 2019

Advances in modelling response styles and related phenomena.

Br J Math Stat Psychol 2019 11;72(3):393-400

Quantitative and Mixed-Methods Research Methodologies, University of Cincinnati, Ohio, USA.

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12190DOI Listing
November 2019

A hierarchical latent response model for inferences about examinee engagement in terms of guessing and item-level non-response.

Br J Math Stat Psychol 2019 Nov 10:e12188. Epub 2019 Nov 10.

Methods and Evaluation/Quality Assurance, Freie Universität Berlin, Germany.

In low-stakes assessments, test performance has few or no consequences for examinees themselves, so that examinees may not be fully engaged when answering the items. Instead of engaging in solution behaviour, disengaged examinees might randomly guess or generate no response at all. When ignored, examinee disengagement poses a severe threat to the validity of results obtained from low-stakes assessments. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12188DOI Listing
November 2019

Deterministic blockmodelling of signed and two-mode networks: A tutorial with software and psychological examples.

Br J Math Stat Psychol 2019 Nov 8. Epub 2019 Nov 8.

University of Missouri, Columbia, Missouri, USA.

Deterministic blockmodelling is a well-established clustering method for both exploratory and confirmatory social network analysis seeking partitions of a set of actors so that actors within each cluster are similar with respect to their patterns of ties to other actors (or, in some cases, other objects when considering two-mode networks). Even though some of the historical foundations for certain types of blockmodelling stem from the psychological literature, applications of deterministic blockmodelling in psychological research are relatively rare. This scarcity is potentially attributable to three factors: a general unfamiliarity with relevant blockmodelling methods and applications; a lack of awareness of the value of partitioning network data for understanding group structures and processes; and the unavailability of such methods on software platforms familiar to most psychological researchers. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12192DOI Listing
November 2019

Bayesian power equivalence in latent growth curve models.

Br J Math Stat Psychol 2019 Nov 5. Epub 2019 Nov 5.

Department of Psychology, University of the Bundeswehr, Germany.

Longitudinal studies are the gold standard for research on time-dependent phenomena in the social sciences. However, they often entail high costs due to multiple measurement occasions and a long overall study duration. It is therefore useful to optimize these design factors while maintaining a high informativeness of the design. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12193DOI Listing
November 2019

Point-biserial correlation: Interval estimation, hypothesis testing, meta-analysis, and sample size determination.

Authors:
Douglas G Bonett

Br J Math Stat Psychol 2019 Sep 30. Epub 2019 Sep 30.

Department of Psychology, University of California, Santa Cruz, California, USA.

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. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12189DOI Listing
September 2019

Marginalized maximum a posteriori estimation for the four-parameter logistic model under a mixture modelling framework.

Br J Math Stat Psychol 2019 Sep 25. Epub 2019 Sep 25.

School of Mathematics and Statistics, KLAS, Northeast Normal University, Changchun, Jilin, China.

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 provides a natural connection with popular cognitive diagnosis models. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12185DOI Listing
September 2019

Combining diversity and dispersion criteria for anticlustering: A bicriterion approach.

Br J Math Stat Psychol 2019 Sep 12. Epub 2019 Sep 12.

University of Missouri, Columbia, Missouri, USA.

Most partitioning methods used in psychological research seek to produce homogeneous groups (i.e., groups with low intra-group dissimilarity). Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12186DOI Listing
September 2019

Confidence interval-based sample size determination formulas and some mathematical properties for hierarchical data.

Authors:
Satoshi Usami

Br J Math Stat Psychol 2019 Sep 7. Epub 2019 Sep 7.

Department of Education, University of Tokyo, Japan.

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. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12181DOI Listing
September 2019

The use of item scores and response times to detect examinees who may have benefited from item preknowledge.

Br J Math Stat Psychol 2019 Aug 16. Epub 2019 Aug 16.

Educational Testing Service, Princeton, New Jersey, USA.

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 set of compromised items is known. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12187DOI Listing

Revisiting dispersion in count data item response theory models: The Conway-Maxwell-Poisson counts model.

Br J Math Stat Psychol 2019 Aug 16. Epub 2019 Aug 16.

Department of Statistics, TU Dortmund University, Germany.

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. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12184DOI Listing

A Latent Gaussian process model for analysing intensive longitudinal data.

Br J Math Stat Psychol 2020 May 16;73(2):237-260. Epub 2019 Aug 16.

Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China.

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 curve analysis that is more suitable for the analysis of intensive longitudinal data than existing latent curve models. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12180DOI Listing

Combining mixture distribution and multidimensional IRTree models for the measurement of extreme response styles.

Br J Math Stat Psychol 2019 11 6;72(3):538-559. Epub 2019 Aug 6.

Polish Academy of Sciences, Warsaw, Poland.

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 direction. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12179DOI Listing
November 2019

A mixture model for responses and response times with a higher-order ability structure to detect rapid guessing behaviour.

Br J Math Stat Psychol 2020 May 6;73(2):261-288. Epub 2019 Aug 6.

Key Laboratory of Applied Statistics of MOE, School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, China.

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 solution behaviour and rapid guessing behaviour. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12175DOI Listing

The counterintuitive impact of responses and response times on parameter estimates in the drift diffusion model.

Authors:
Pascal Jordan

Br J Math Stat Psychol 2020 May 21;73(2):289-315. Epub 2019 Jul 21.

University of Hamburg, Germany.

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 reverse implication does not hold for the estimates: shorter response times can decrease the drift rate estimate. Read More

View Article

Download full-text PDF

Source
https://onlinelibrary.wiley.com/doi/abs/10.1111/bmsp.12183
Publisher Site
http://dx.doi.org/10.1111/bmsp.12183DOI Listing
May 2020
3 Reads

Evaluation on types of invariance in studying extreme response bias with an IRTree approach.

Br J Math Stat Psychol 2019 11 10;72(3):517-537. Epub 2019 Jul 10.

Department of Psychology, Ohio State University, Columbus, Ohio, USA.

In recent years, item response tree (IRTree) approaches have received increasing attention in the response style literature for their ability to partial out response style latent variables as well as associated item parameters. When an IRTree approach is adopted to measure extreme response styles, directional and content invariance could be assumed at the latent variable and item parameter levels. In this study, we propose to evaluate the empirical validity of these invariance assumptions by employing a general IRTree model with relaxed invariance assumptions. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12182DOI Listing
November 2019

Standard errors of two-level scalability coefficients.

Br J Math Stat Psychol 2020 May 23;73(2):213-236. Epub 2019 Jun 23.

Research Institute of Child Development and Education, University of Amsterdam, The Netherlands.

For the construction of tests and questionnaires that require multiple raters (e.g., a child behaviour checklist completed by both parents) a novel ordinal scaling technique is currently being further developed, called two-level Mokken scale analysis. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12174DOI Listing

Back to the basics: Rethinking partial correlation network methodology.

Br J Math Stat Psychol 2020 May 17;73(2):187-212. Epub 2019 Jun 17.

University of California, Davis, California, USA.

The Gaussian graphical model (GGM) is an increasingly popular technique used in psychology to characterize relationships among observed variables. These relationships are represented as elements in the precision matrix. Standardizing the precision matrix and reversing the sign yields corresponding partial correlations that imply pairwise dependencies in which the effects of all other variables have been controlled for. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12173DOI Listing
May 2020
9 Reads

Testing two variances for superiority/non-inferiority and equivalence: Using the exhaustion algorithm for sample size allocation with cost.

Br J Math Stat Psychol 2020 May 12;73(2):316-332. Epub 2019 Jun 12.

Institute of Education, National Cheng Kung University, Tainan, Taiwan.

The equality of two group variances is frequently tested in experiments. However, criticisms of null hypothesis statistical testing on means have recently arisen and there is interest in other types of statistical tests of hypotheses, such as superiority/non-inferiority and equivalence. Although these tests have become more common in psychology and social sciences, the corresponding sample size estimation for these tests is rarely discussed, especially when the sampling unit costs are unequal or group sizes are unequal for two groups. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12172DOI Listing
May 2020
1 Read

Interval estimation for linear functions of medians in within-subjects and mixed designs.

Br J Math Stat Psychol 2020 May 7;73(2):333-346. Epub 2019 May 7.

Department of Mathematics and Statistics, East Tennessee State University, Johnson City, Tennessee, USA.

The currently available distribution-free confidence interval for a difference of medians in a within-subjects design requires an unrealistic assumption of identical distribution shapes. A confidence interval for a general linear function of medians is proposed for within-subjects designs that do not assume identical distribution shapes. The proposed method can be combined with a method for linear functions of independent medians to provide a confidence interval for a linear function of medians in mixed designs. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12171DOI Listing
May 2020
2 Reads

Hubert's multi-rater kappa revisited.

Br J Math Stat Psychol 2020 02 6;73(1):1-22. Epub 2019 May 6.

Centro Universitario de la Defensa - ENM, Universidad de Vigo, Vigo, Pontevedra, Spain.

There is a frequent need to measure the degree of agreement among R observers who independently classify n subjects within K nominal or ordinal categories. The most popular methods are usually kappa-type measurements. When R = 2, Cohen's kappa coefficient (weighted or not) is well known. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12167DOI Listing
February 2020
3 Reads

Bayesian generalized structured component analysis.

Br J Math Stat Psychol 2020 May 2;73(2):347-373. Epub 2019 May 2.

McGill University, Montreal, Quebec, Canada.

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modelling, which adopts components of observed variables as proxies for latent variables and examines directional relationships among latent and observed variables. GSCA has been extended to deal with a wider range of data types, including discrete, multilevel or intensive longitudinal data, as well as to accommodate a greater variety of complex analyses such as latent moderation analysis, the capturing of cluster-level heterogeneity, and regularized analysis. To date, however, there has been no attempt to generalize the scope of GSCA into the Bayesian framework. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12166DOI Listing
May 2020
2 Reads

Clustering preference data in the presence of response-style bias.

Br J Math Stat Psychol 2019 11 2;72(3):401-425. Epub 2019 May 2.

Facluty of Culture and Information Science, Doshisha University, Japan.

Preference data, such as Likert scale data, are often obtained in questionnaire-based surveys. Clustering respondents based on survey items is useful for discovering latent structures. However, cluster analysis of preference data may be affected by response styles, that is, a respondent's systematic response tendencies irrespective of the item content. Read More

View Article

Download full-text PDF

Source
https://onlinelibrary.wiley.com/doi/abs/10.1111/bmsp.12170
Publisher Site
http://dx.doi.org/10.1111/bmsp.12170DOI Listing
November 2019
18 Reads

Comparison of classical and modern methods for measuring and correcting for acquiescence.

Br J Math Stat Psychol 2019 11 29;72(3):447-465. Epub 2019 Apr 29.

EduLab21, Ayrton Senna Institute, São Paulo, Brazil.

Likert-type self-report scales are frequently used in large-scale educational assessment of social-emotional skills. Self-report scales rely on the assumption that their items elicit information only about the trait they are supposed to measure. However, different response biases may threaten this assumption. Read More

View Article

Download full-text PDF

Source
https://onlinelibrary.wiley.com/doi/abs/10.1111/bmsp.12168
Publisher Site
http://dx.doi.org/10.1111/bmsp.12168DOI Listing
November 2019
4 Reads

Using multidimensional item response theory to evaluate how response styles impact measurement.

Br J Math Stat Psychol 2019 11 28;72(3):466-485. Epub 2019 Mar 28.

Department of Medicine, University of Wisconsin, Madison, Wisconsin, USA.

Multidimensional item response theory (MIRT) models for response style (e.g., Bolt, Lu, & Kim, 2014, Psychological Methods, 19, 528; Falk & Cai, 2016, Psychological Methods, 21, 328) provide flexibility in accommodating various response styles, but often present difficulty in isolating the effects of response style(s) from the intended substantive trait(s). Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12169DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6765459PMC
November 2019
2 Reads

Look-ahead content balancing method in variable-length computerized classification testing.

Br J Math Stat Psychol 2020 02 26;73(1):88-108. Epub 2019 Mar 26.

Educational Psychology & Research Methodology, College of Education, Purdue University, West Lafayette, Indiana, USA.

Content balancing is one of the most important issues in computerized classification testing. To adapt to variable-length forms, special treatments are needed to successfully control content constraints without knowledge of test length during the test. To this end, we propose the notions of 'look-ahead' and 'step size' to adaptively control content constraints in each item selection step. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12165DOI Listing
February 2020
2 Reads

Assessing item-feature effects with item response tree models.

Authors:
Ulf Böckenholt

Br J Math Stat Psychol 2019 11 26;72(3):486-500. Epub 2019 Mar 26.

Kellogg School of Management, Northwestern University, Evanston, Illinois, USA.

Recent applications of item response tree models demonstrate that this model class is well suited to detect midpoint and extremity response style effects in both attitudinal and personality measurements. This paper proposes an extension of this approach that goes beyond measuring response styles and allows us to examine item-feature effects. In a reanalysis of three published data sets, it is shown that the proposed extension captures item-feature effects across affirmative and reverse-worded items in a psychological test. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12163DOI Listing
November 2019
2 Reads

When is the Wilcoxon-Mann-Whitney procedure a test of location? Implications for effect-size measures.

Br J Math Stat Psychol 2020 02 21;73(1):170-183. Epub 2019 Mar 21.

Department of Mathematics and Statistics, American University, Washington, District of Columbia.

The Wilcoxon-Mann-Whitney procedure is invariant under monotone transformations but its use as a test of location or shift is said not to be so. It tests location only under the shift model, the assumption of parallel cumulative distribution functions (cdfs). We show that infinitely many monotone transformations of the measured variable produce parallel cdfs, so long as the original cdfs intersect nowhere or everywhere. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12162DOI Listing
February 2020
2 Reads

Dynamic estimation in the extended marginal Rasch model with an application to mathematical computer-adaptive practice.

Br J Math Stat Psychol 2020 02 18;73(1):72-87. Epub 2019 Mar 18.

ACTNext, Iowa City, Iowa, USA.

We introduce a general response model that allows for several simple restrictions, resulting in other models such as the extended Rasch model. For the extended Rasch model, a dynamic Bayesian estimation procedure is provided, which is able to deal with data sets that change over time, and possibly include many missing values. To ensure comparability over time, a data augmentation method is used, which provides an augmented person-by-item data matrix and reproduces the sufficient statistics of the complete data matrix. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12157DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7003866PMC
February 2020
2 Reads

Individual, situational, and cultural correlates of acquiescent responding: Towards a unified conceptual framework.

Br J Math Stat Psychol 2019 11 9;72(3):426-446. Epub 2019 Mar 9.

Department of Survey Design and Methodology, GESIS - Leibniz Institute for the Social Sciences, Mannheim, Germany.

Acquiescence ('yea-saying') can seriously harm the validity of self-report questionnaire data. Towards a better understanding of why some individuals and groups acquiesce more strongly than others do, we developed a unified conceptual framework of acquiescent responding. Our framework posits that acquiescent responding is a joint function of respondent characteristics (e. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12164DOI Listing
November 2019
2 Reads

Utilizing response times in cognitive diagnostic computerized adaptive testing under the higher-order deterministic input, noisy 'and' gate model.

Authors:
Hung-Yu Huang

Br J Math Stat Psychol 2020 02 22;73(1):109-141. Epub 2019 Feb 22.

Department of Psychology and Counseling, University of Taipei, Taiwan.

Methods of cognitive diagnostic computerized adaptive testing (CD-CAT) under higher-order cognitive diagnosis models have been developed to simultaneously provide estimates of the attribute mastery statuses of examinees for formative assessment and estimates of a latent continuous trait for overall summative evaluation. In a typical CD-CAT environment, examinees are often subject to a time limit, and the examinees' response times (RTs) for specific test items can be routinely recorded by custom-made programs. Because examinees are individually administered tailored sets of test items from the item pool, they may experience different levels of speededness during testing and different levels of risk of running out of time. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12160DOI Listing
February 2020
3 Reads

Towards end-to-end likelihood-free inference with convolutional neural networks.

Br J Math Stat Psychol 2020 02 22;73(1):23-43. Epub 2019 Feb 22.

Heidelberg Collaboratory for Image Processing (HCI), Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Germany.

Complex simulator-based models with non-standard sampling distributions require sophisticated design choices for reliable approximate parameter inference. We introduce a fast, end-to-end approach for approximate Bayesian computation (ABC) based on fully convolutional neural networks. The method enables users of ABC to derive simultaneously the posterior mean and variance of multidimensional posterior distributions directly from raw simulated data. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12159DOI Listing
February 2020
2 Reads

Cognitive diagnosis models for multiple strategies.

Br J Math Stat Psychol 2019 05 12;72(2):370-392. Epub 2019 Feb 12.

Department of Educational Studies in Psychology, Research Methodology and Counseling, The University of Alabama, Tuscaloosa, Alabama, USA.

Cognitive diagnosis models (CDMs) have been used as psychometric tools in educational assessments to estimate students' proficiency profiles. However, most CDMs assume that all students adopt the same strategy when approaching problems in an assessment, which may not be the case in practice. This study develops a generalized multiple-strategy CDM for dichotomous response data. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12155DOI Listing
May 2019
3 Reads

A note on residual M-distances for identifying aberrant response patterns.

Br J Math Stat Psychol 2020 02 12;73(1):164-169. Epub 2019 Feb 12.

University of Giessen, Germany.

Although a statistical model might fit well to a large proportion of the individuals of a random sample, some individuals might give 'unusual' responses that are not well explained by the hypothesized model. If individual responses are given as continuous response vectors, M-distances can be used to produce real valued indicators of how well an individual's response vector corresponds to a covariance structure implied by a psychometric model. In this note, we focus on the so-called one-factor model. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12161DOI Listing
February 2020
2 Reads

IRTree models with ordinal and multidimensional decision nodes for response styles and trait-based rating responses.

Br J Math Stat Psychol 2019 11 12;72(3):501-516. Epub 2019 Feb 12.

University of Mannheim, Germany.

IRTree models decompose observed rating responses into sequences of theory-based decision nodes, and they provide a flexible framework for analysing trait-related judgements and response styles. However, most previous applications of IRTree models have been limited to binary decision nodes that reflect qualitatively distinct and unidimensional judgement processes. The present research extends the family of IRTree models for the analysis of response styles to ordinal judgement processes for polytomous decisions and to multidimensional parametrizations of decision nodes. Read More

View Article

Download full-text PDF

Source
http://doi.wiley.com/10.1111/bmsp.12158
Publisher Site
http://dx.doi.org/10.1111/bmsp.12158DOI Listing
November 2019
3 Reads

An empirical Q-matrix validation method for the sequential generalized DINA model.

Br J Math Stat Psychol 2020 02 5;73(1):142-163. Epub 2019 Feb 5.

Faculty of Education, University of Hong Kong, Hong Kong.

As a core component of most cognitive diagnosis models, the Q-matrix, or item and attribute association matrix, is typically developed by domain experts, and tends to be subjective. It is critical to validate the Q-matrix empirically because a misspecified Q-matrix could result in erroneous attribute estimation. Most existing Q-matrix validation procedures are developed for dichotomous responses. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12156DOI Listing
February 2020
2 Reads

Analysing multisource feedback with multilevel structural equation models: Pitfalls and recommendations from a simulation study.

Br J Math Stat Psychol 2019 05 29;72(2):294-315. Epub 2019 Jan 29.

Division of Methods and Evaluation, Department of Educational Science and Psychology, Freie Universität Berlin, Germany.

When multisource feedback instruments, for example, 360-degree feedback tools, are validated, multilevel structural equation models are the method of choice to quantify the amount of reliability as well as convergent and discriminant validity. A non-standard multilevel structural equation model that incorporates self-ratings (level-2 variables) and others' ratings from different additional perspectives (level-1 variables), for example, peers and subordinates, has recently been presented. In a Monte Carlo simulation study, we determine the minimal required sample sizes for this model. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12149DOI Listing
May 2019
3 Reads

An improved stochastic EM algorithm for large-scale full-information item factor analysis.

Br J Math Stat Psychol 2020 02 3;73(1):44-71. Epub 2018 Dec 3.

Department of Human Development and Quantitative Methodology, University of Maryland, College Park MD.

In this paper, we explore the use of the stochastic EM algorithm (Celeux & Diebolt (1985) Computational Statistics Quarterly, 2, 73) for large-scale full-information item factor analysis. Innovations have been made on its implementation, including an adaptive-rejection-based Gibbs sampler for the stochastic E step, a proximal gradient descent algorithm for the optimization in the M step, and diagnostic procedures for determining the burn-in size and the stopping of the algorithm. These developments are based on the theoretical results of Nielsen (2000, Bernoulli, 6, 457), as well as advanced sampling and optimization techniques. Read More

View Article

Download full-text PDF

Source
http://doi.wiley.com/10.1111/bmsp.12153
Publisher Site
http://dx.doi.org/10.1111/bmsp.12153DOI Listing
February 2020
33 Reads

Asymptotic bias of normal-distribution-based maximum likelihood estimates of moderation effects with data missing at random.

Br J Math Stat Psychol 2019 05 25;72(2):334-354. Epub 2018 Nov 25.

University of Notre Dame, Indiana, USA.

Moderation analysis is useful for addressing interesting research questions in social sciences and behavioural research. In practice, moderated multiple regression (MMR) models have been most widely used. However, missing data pose a challenge, mainly because the interaction term is a product of two or more variables and thus is a non-linear function of the involved variables. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1111/bmsp.12151DOI Listing
May 2019
3 Reads