A Logistic IRT Model for Decreasing and Increasing Item Characteristic Curves

2001 ◽  
pp. 173-192 ◽  
Author(s):  
Edwin L. Klinkenberg
Keyword(s):  
Characteristic Curves ◽  
Irt Model

The Effect of Alternative Scoring Procedures on the Measurement Properties of a Self-Administered Depression Scale

2019 ◽  
Vol 35 (1) ◽  
pp. 55-62 ◽  
Author(s):  
Noboru Iwata ◽  
Akizumi Tsutsumi ◽  
Takafumi Wakita ◽  
Ryuichi Kumagai ◽  
Hiroyuki Noguchi ◽  
...  
Keyword(s):  
Classical Test Theory ◽  
Depression Scale ◽  
Psychometric Testing ◽  
Epidemiologic Studies ◽  
Test Theory ◽  
Measurement Properties ◽  
Irt Model ◽  
Response Alternatives ◽  
Polytomous Item Response ◽  
Θ Point

Abstract. To investigate the effect of response alternatives/scoring procedures on the measurement properties of the Center for Epidemiologic Studies Depression Scale (CES-D) which has the four response alternatives, a polytomous item response theory (IRT) model was applied to the responses of 2,061 workers and university students (1,640 males, 421 females). Test information functions derived from the polytomous IRT analyses on the CES-D data with various scoring procedures indicated that: (1) the CES-D with its standard (0-1-2-3) scoring procedure should be useful for screening to detect subjects with “at high-risk” of depression if the θ point showing the highest information corresponds to the cut-off point, because of its extremely higher information; (2) the CES-D with the 0-1-1-2 scoring procedure could cover wider range of depressive severity, suggesting that this scoring procedure might be useful in cases where more exhaustive discrimination in symptomatology is of interest; and (3) the revised version of CES-D with replacing original positive items into negatively revised items outperformed the original version. These findings have never been demonstrated by the classical test theory analyses, and thus the utility of this kind of psychometric testing should be warranted to further investigation for the standard measures of psychological assessment.

Modeling Self-Determination Theory Motivation Data by Using Unfolding IRT

2020 ◽  
pp. 1-9
Author(s):  
Philipp A. Freund ◽  
Annette Lohbeck
Keyword(s):  
Ideal Point ◽  
Self Determination Theory ◽  
Self Determination ◽  
Dominance Model ◽  
Irt Model ◽  
Autonomous Behavior ◽  
Location Parameters ◽  
Unfolding Models ◽  
Using Data ◽  
Item Location

Abstract. Self-determination theory (SDT) suggests that the degree of autonomous behavior regulation is a characteristic of distinct motivation types which thus can be ordered on the so-called Autonomy-Control Continuum (ACC). The present study employs an item response theory (IRT) model under the ideal point response/unfolding paradigm in order to model the response process to SDT motivation items in theoretical accordance with the ACC. Using data from two independent student samples (measuring SDT motivation for the academic subjects of Mathematics and German as a native language), it was found that an unfolding model exhibited a relatively better fit compared to a dominance model. The item location parameters under the unfolding paradigm showed clusters of items representing the different regulation types on the ACC to be (almost perfectly) empirically separable, as suggested by SDT. Besides theoretical implications, perspectives for the application of ideal point response/unfolding models in the development of measures for non-cognitive constructs are addressed.

scholarly journals Investigating the Impact of Noneffortful Responses on Individual-Level Scores: Can the Effort-Moderated IRT Model Serve as a Solution?

2021 ◽  
pp. 014662162110138
Author(s):  
Joseph A. Rios ◽  
James Soland
Keyword(s):  
Classification Accuracy ◽  
Negative Impact ◽  
Parameter Recovery ◽  
Individual Level ◽  
Irt Model ◽  
Ability Estimates ◽  
Misclassification Rates ◽  
Individual Scores ◽  
3Pl Model ◽  
The Impact

Suboptimal effort is a major threat to valid score-based inferences. While the effects of such behavior have been frequently examined in the context of mean group comparisons, minimal research has considered its effects on individual score use (e.g., identifying students for remediation). Focusing on the latter context, this study addressed two related questions via simulation and applied analyses. First, we investigated how much including noneffortful responses in scoring using a three-parameter logistic (3PL) model affects person parameter recovery and classification accuracy for noneffortful responders. Second, we explored whether improvements in these individual-level inferences were observed when employing the Effort Moderated IRT (EM-IRT) model under conditions in which its assumptions were met and violated. Results demonstrated that including 10% noneffortful responses in scoring led to average bias in ability estimates and misclassification rates by as much as 0.15 SDs and 7%, respectively. These results were mitigated when employing the EM-IRT model, particularly when model assumptions were met. However, once model assumptions were violated, the EM-IRT model’s performance deteriorated, though still outperforming the 3PL model. Thus, findings from this study show that (a) including noneffortful responses when using individual scores can lead to potential unfounded inferences and potential score misuse, and (b) the negative impact that noneffortful responding has on person ability estimates and classification accuracy can be mitigated by employing the EM-IRT model, particularly when its assumptions are met.

scholarly journals Computer-based application for high school physics exams using IRT model 1P

2021 ◽  
Author(s):  
Yetti Supriyati ◽  
Dwi Susanti ◽  
Slamet Maulana
Keyword(s):  
High School ◽  
Irt Model ◽  
High School Physics ◽  
Computer Based

A conditional approach for the receiver operating characteristic curve construction to evaluate diagnostic test performance in a family-matched case–control design

2021 ◽  
pp. 096228022199595
Author(s):  
Yalda Zarnegarnia ◽  
Shari Messinger
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Case Control ◽  
Paired Data ◽  
Characteristic Curves ◽  
Receiver Operating Characteristic Curves ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Receiver operating characteristic curves are widely used in medical research to illustrate biomarker performance in binary classification, particularly with respect to disease or health status. Study designs that include related subjects, such as siblings, usually have common environmental or genetic factors giving rise to correlated biomarker data. The design could be used to improve detection of biomarkers informative of increased risk, allowing initiation of treatment to stop or slow disease progression. Available methods for receiver operating characteristic construction do not take advantage of correlation inherent in this design to improve biomarker performance. This paper will briefly review some developed methods for receiver operating characteristic curve estimation in settings with correlated data from case–control designs and will discuss the limitations of current methods for analyzing correlated familial paired data. An alternative approach using conditional receiver operating characteristic curves will be demonstrated. The proposed approach will use information about correlation among biomarker values, producing conditional receiver operating characteristic curves that evaluate the ability of a biomarker to discriminate between affected and unaffected subjects in a familial paired design.

scholarly journals Derivation of water flooding characteristic curve for offshore low-amplitude structural reservoir with strong bottom water

2021 ◽  
Author(s):  
Ying-xian Liu ◽  
Jie Tan ◽  
Hui Cai ◽  
Yan-lai Li ◽  
Chun-yan Liu
Keyword(s):  
Bottom Water ◽  
Characteristic Curve ◽  
Calculated Data ◽  
Oil Production ◽  
Water Flooding ◽  
Characteristic Curves ◽  
Recoverable Reserves ◽  
Curve Method ◽  
Water Cut ◽  
Low Amplitude

AbstractThe water flooding characteristic curve method is one of the essential techniques to predict recoverable reserves. However, the recoverable reserves indicated by the existing water flooding characteristic curves of low-amplitude reservoirs with strong bottom water increase gradually, and the current local recovery degree of some areas has exceeded the predicted recovery rate. The applicability of the existing water flooding characteristic curves in low-amplitude reservoirs with strong bottom water is lacking, which affects the accurate prediction of development performance. By analyzing the derivation process of the conventional water flooding characteristic curve method, this manuscript finds out the reasons for the poor applicability of the existing water flooding characteristic curve in low-amplitude reservoir with strong bottom water and corrects the existing water flooding characteristic curve according to the actual situation of the oilfield and obtains the improvement method of water flooding characteristic curve in low-amplitude reservoir with strong bottom water. After correction, the correlation coefficient between $$\frac{{k_{ro} }}{{k_{rw} }}$$ k ro k rw and $$S_{w}$$ S w is 95.92%. According to the comparison between the actual data and the calculated data, in 2021/3, the actual water cut is 97.29%, the water cut predicted by the formula is 97.27%, the actual cumulative oil production is 31.19 × 104t, and the predicted cumulative oil production is 31.31 × 104t. The predicted value is consistent with the actual value. It provides a more reliable method for predicting low-amplitude reservoirs' recoverable ability with strong bottom water and guides the oilfield's subsequent decision-making.

Sign in / Sign up

Export Citation Format

Share Document