Brian C Leventhal
Biographic Data
| ID | 8867130 |
|---|---|
| NAME | Brian C Leventhal |
| GIVEN NAMES | Brian C |
| FAMILY NAME | Leventhal |
| SIGNATURE | LEVENTHAL B C |
| AFFILIATIONS | James Madison University, Harrisonburg, VA, USA |
| ORCID | 0000-0002-6480-2016 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
An Illustration of an IRTree Model for Disengagement
Low-stakes test performance commonly reflects examinee ability and effort. Examinees exhibiting low effort may be identified through rapid guessing behavior throughout an assessment. There has been a plethora of methods proposed to adjust scores once rapid guesses have been identified, but these have been plagued by strong assumptions or the removal of examinees. In this study, we illustrate how an IRTree model can be used to adjust examinee abil…
Modeling Changes in Response Style with Longitudinal IRTree Models
Traditional psychometric modeling focuses on observed categorical item responses, which can over-simplify the respondent cognitive response process. A further weakness is that analysis of ordinal responses has been primarily limited to a single substantive trait at one time point. We propose a significant expansion of this modeling framework to account for complex response processes across multiple waves of data collection using the beneficial it…
Seeing the Forest and the Trees
In this study, we examined the results and interpretations produced from two different IRTree models-one using paths consisting of only dichotomous decisions, and one using paths consisting of both dichotomous and polytomous decisions. We used data from two versions of an impulsivity measure. In the first version, all the response options had labels; in the second version, only the endpoints were labeled. Based on past research, we hypothesized t…
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Seeing the Forest and the Trees
In this study, we examined the results and interpretations produced from two different IRTree models-one using paths consisting of only dichotomous decisions, and one using paths consisting of both dichotomous and polytomous decisions. We used data from two versions of an impulsivity measure. In the first version, all the response options had labels; in the second version, only the endpoints were labeled. Based on past research, we hypothesized t…
Modeling Changes in Response Style with Longitudinal IRTree Models
Traditional psychometric modeling focuses on observed categorical item responses, which can over-simplify the respondent cognitive response process. A further weakness is that analysis of ordinal responses has been primarily limited to a single substantive trait at one time point. We propose a significant expansion of this modeling framework to account for complex response processes across multiple waves of data collection using the beneficial it…
An Illustration of an IRTree Model for Disengagement
Low-stakes test performance commonly reflects examinee ability and effort. Examinees exhibiting low effort may be identified through rapid guessing behavior throughout an assessment. There has been a plethora of methods proposed to adjust scores once rapid guesses have been identified, but these have been plagued by strong assumptions or the removal of examinees. In this study, we illustrate how an IRTree model can be used to adjust examinee abil…
Computer Science (3 works) · Econometrics (3 works) · Item response theory (3 works) · Mathematics (3 works) · Psychology (3 works) · Psychometrics (3 works) · Statistics (3 works) · Developmental psychology (2 works) · Psychometric Methodologies and Testing (2 works) · Sample (material) (2 works)