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Restricted Latent Class Models for Nominal Response Data: Identifiability and Estimation
Restricted latent class models (RLCMs) provide an important framework for diagnosing and classifying respondents on a collection of multivariate...
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What Can We Learn from a Semiparametric Factor Analysis of Item Responses and Response Time? An Illustration with the PISA 2015 Data
It is widely believed that a joint factor analysis of item responses and response time (RT) may yield more precise ability scores that are...
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Bi-factor and Second-Order Copula Models for Item Response Data
Bi-factor and second-order models based on copulas are proposed for item response data, where the items are sampled from identified subdomains of...
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Semiparametric Factor Analysis for Item-Level Response Time Data
Item-level response time (RT) data can be conveniently collected from computer-based test/survey delivery platforms and have been demonstrated to...
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Bayesian Model Assessment for Jointly Modeling Multidimensional Response Data with Application to Computerized Testing
Computerized assessment provides rich multidimensional data including trial-by-trial accuracy and response time (RT) measures. A key question in...
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Prioritising interventions for preventing mental health problems for children experiencing adversity: a modified nominal group technique Australian consensus study
BackgroundDespite the well-established link between childhood adversity and mental health problems, there is a dearth of evidence to inform decision...
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Parallelism Between Sentence Structure and Nominal Phrases in Japanese: Evidence from Scrambled Instrumental and Locative Adverbial Phrases
The present study investigated the canonical position of instrumental and locative adverbial phrases in both Japanese sentences and noun phrases to...
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Ordinal Outcome State-Space Models for Intensive Longitudinal Data
Intensive longitudinal (IL) data are increasingly prevalent in psychological science, coinciding with technological advancements that make it simple...
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Normative Data for Novel Nominal Metaphors, Novel Similes, Literal, and Anomalous Utterances in Polish and English
The two studies reported in the article provide normative measures for 120 novel nominal metaphors, 120 novel similes, 120 literal sentences, and 120...
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Testing delayed, gradual, and temporary treatment effects in randomized single-case experiments: A general response function framework
Randomization tests represent a class of significance tests to assess the statistical significance of treatment effects in randomized single-case...
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Distorted correlations among censored data: causes, effects, and correction
Data censoring occurs when researchers do not know precise values of data points (e.g., age is 55+ or concentration ≤ .001). Censoring is frequent...
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Multilevel modeling in single-case studies with zero-inflated and overdispersed count data
Count outcomes are frequently encountered in single-case experimental designs (SCEDs). Generalized linear mixed models (GLMMs) have shown promise in...
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Statistical approaches to identifying lapses in psychometric response data
Psychometric curve fits relate physical stimuli to an observer’s performance. In experiments an observer may “lapse” and respond with a random guess,...
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A cognitive model of response omissions in distraction paradigms
The effects of distraction on responses manifest in three ways: prolonged reaction times, and increased error and response omission rates. However,...
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The analysis of randomized response “ever” and “last year” questions: A non-saturated Multinomial model
Randomized response (RR) is a well-known interview technique designed to eliminate evasive response bias that arises from asking sensitive questions....
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Longitudinal joint modeling for assessing parallel interactive development of latent ability and processing speed using responses and response times
To measure the parallel interactive development of latent ability and processing speed using longitudinal item response accuracy (RA) and...
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Dealing with missing data in multi-informant studies: A comparison of approaches
Multi-informant studies are popular in social and behavioral science. However, their data analyses are challenging because data from different...
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Model-agnostic unsupervised detection of bots in a Likert-type questionnaire
To detect bots in online survey data, there is a wealth of literature on statistical detection using only responses to Likert-type items. There are...
