scholarly journals Cognitively Diagnostic Assessments and the Cognitive Diagnosis Model Framework

2014 ◽  
Vol 20 (2) ◽  
pp. 89-97 ◽  
Author(s):  
Jimmy de la Torre ◽  
Nathan Minchen
Keyword(s):  
Cognitive Diagnosis ◽  
Model Framework ◽  
Diagnosis Model ◽  
Cognitively Diagnostic ◽  
Cognitive Diagnosis Model

scholarly journals The CDA-BPD: retrofitting a traditional borderline personality questionnaire under the cognitive diagnosis model framework

2019 ◽  
Vol 13 ◽  
Author(s):  
Siwei Peng ◽  
Daxun Wang ◽  
Xuliang Gao ◽  
Yan Cai ◽  
Dongbo Tu
Keyword(s):  
Borderline Personality Disorder ◽  
Personality Disorder ◽  
Borderline Personality ◽  
Cognitive Diagnosis ◽  
General Level ◽  
Personality Questionnaire ◽  
Model Framework ◽  
Level Information ◽  
Diagnosis Model ◽  
Cognitive Diagnosis Model

Abstract To obtain rich information about the cognitive diagnosis of borderline personality disorder (BPD), this study attempted to retrofit a traditional borderline personality questionnaire so that the improved assessment (called CDA-BPD) could provide more diagnostic information. The retrofitting processes included the following steps: (1) applied an cognitive diagnosis model to analyze the psychometric characteristics of the traditional questionnaire; (2) under the guidance of cognitive diagnosis assessment (CDA), high-quality items were chosen to develop the CDA-BPD and tested on 1,097 subjects; (3) the quality of the CDA-BPD was evaluated; (4) the structure of the CDA-BPD was analyzed. Results indicated that: (1) the CDA-BPD had acceptable reliability and validity; (2) the CDA-BPD had sensitivity of 0.985 and specificity of 0.853 with area under curve (AUC) = 0.956; (3) the two structural factors of the traditional questionnaire were confirmed in the CDA-BPD; χ2 was 83.01 with df = 26, p < .0001, comparative fit index (CFI) = 0.97, root mean square error of approximation (RMSEA) = 0.045. It was concluded that the practice of retrofitting a traditional borderline personality assessment for cognitive diagnostic purpose was feasible. Most importantly, under the cognitive diagnosis model framework, CDA-BPD could simultaneously provide general-level information and the detailed symptom criteria-level information about the posterior probability of satisfying each symptom criterion in the Diagnostic and Statistical Manual of Mental Disorders (5th edition; DSM-5; American Psychiatric Association, 2013) for each individual, which gave further insight into tailoring individual-specific treatments for borderline personality disorder.

A Cognitive Diagnosis Model for Continuous Response

2017 ◽  
Vol 42 (6) ◽  
pp. 651-677 ◽  
Author(s):  
Nathan D. Minchen ◽  
Jimmy de la Torre ◽  
Ying Liu
Keyword(s):  
Cognitive Diagnosis ◽  
Continuous Response ◽  
Diagnosis Model ◽  
Cognitive Diagnosis Model

scholarly journals Exploring Multiple Strategic Problem Solving Behaviors in Educational Psychology Research by Using Mixture Cognitive Diagnosis Model

2021 ◽  
Vol 12 ◽  
Author(s):  
Jiwei Zhang ◽  
Jing Lu ◽  
Jing Yang ◽  
Zhaoyuan Zhang ◽  
Shanshan Sun
Keyword(s):  
Problem Solving ◽  
Diagnostic Testing ◽  
Cognitive Diagnosis ◽  
Mcmc Algorithm ◽  
Multiple Strategies ◽  
Dina Model ◽  
Single Strategy ◽  
Diagnosis Model ◽  
Multiple Strategy ◽  
Cognitive Diagnosis Model

A mixture cognitive diagnosis model (CDM), which is called mixture multiple strategy-Deterministic, Inputs, Noisy “and” Gate (MMS-DINA) model, is proposed to investigate individual differences in the selection of response categories in multiple-strategy items. The MMS-DINA model system is an effective psychometric and statistical approach consisting of multiple strategies for practical skills diagnostic testing, which not only allows for multiple strategies of problem solving, but also allows for different strategies to be associated with different levels of difficulty. A Markov chain Monte Carlo (MCMC) algorithm for parameter estimation is given to estimate model, and four simulation studies are presented to evaluate the performance of the MCMC algorithm. Based on the available MCMC outputs, two Bayesian model selection criteria are computed for guiding the choice of the single strategy DINA model and multiple strategy DINA models. An analysis of fraction subtraction data is provided as an illustration example.

Sign in / Sign up

Export Citation Format

Share Document