Comparison of Exposure Controls, Item Pool Characteristics, and Population Distributions for CAT Using the Partial Credit Model

2011 ◽  
Vol 72 (1) ◽  
pp. 159-175 ◽  
Author(s):  
HwaYoung Lee ◽  
Barbara G. Dodd
Keyword(s):  
Partial Credit Model ◽  
Item Pool ◽  
Partial Credit ◽  
Population Distributions

scholarly journals Scale Alignment in the Between-Item Multidimensional Partial Credit Model

2021 ◽  
pp. 014662162110131
Author(s):  
Leah Feuerstahler ◽  
Mark Wilson
Keyword(s):  
Item Response ◽  
Kindergarten Readiness ◽  
Latent Trait ◽  
Individual Development ◽  
Partial Credit Model ◽  
Partial Credit ◽  
Response Models ◽  
Item Response Models ◽  
Item Parameters ◽  
Polytomous Item Response

In between-item multidimensional item response models, it is often desirable to compare individual latent trait estimates across dimensions. These comparisons are only justified if the model dimensions are scaled relative to each other. Traditionally, this scaling is done using approaches such as standardization—fixing the latent mean and standard deviation to 0 and 1 for all dimensions. However, approaches such as standardization do not guarantee that Rasch model properties hold across dimensions. Specifically, for between-item multidimensional Rasch family models, the unique ordering of items holds within dimensions, but not across dimensions. Previously, Feuerstahler and Wilson described the concept of scale alignment, which aims to enforce the unique ordering of items across dimensions by linearly transforming item parameters within dimensions. In this article, we extend the concept of scale alignment to the between-item multidimensional partial credit model and to models fit using incomplete data. We illustrate this method in the context of the Kindergarten Individual Development Survey (KIDS), a multidimensional survey of kindergarten readiness used in the state of Illinois. We also present simulation results that demonstrate the effectiveness of scale alignment in the context of polytomous item response models and missing data.

Using Item Response Theory Models to Evaluate the Practice Environment Scale

2014 ◽  
Vol 22 (2) ◽  
pp. 323-341 ◽  
Author(s):  
Dheeraj Raju ◽  
Xiaogang Su ◽  
Patricia A. Patrician
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Information Criterion ◽  
Partial Credit Model ◽  
Practice Environment ◽  
Partial Credit ◽  
Response Theory ◽  
Environment Scale ◽  
Graded Response ◽  
Item Response Theory Models

Background and Purpose: The purpose of this article is to introduce different types of item response theory models and to demonstrate their usefulness by evaluating the Practice Environment Scale. Methods: Item response theory models such as constrained and unconstrained graded response model, partial credit model, Rasch model, and one-parameter logistic model are demonstrated. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) indices are used as model selection criterion. Results: The unconstrained graded response and partial credit models indicated the best fit for the data. Almost all items in the instrument performed well. Conclusions: Although most of the items strongly measure the construct, there are a few items that could be eliminated without substantially altering the instrument. The analysis revealed that the instrument may function differently when administered to different unit types.

scholarly journals Translation and Psychometric Evaluation of the Dutch Families Importance in Nursing Care: Nurses’ Attitudes Scale Based on the Generalized Partial Credit Model

2018 ◽  
Vol 24 (4) ◽  
pp. 538-562 ◽  
Author(s):  
E. I. Hagedoorn ◽  
W. Paans ◽  
T. Jaarsma ◽  
J. C. Keers ◽  
C. P. van der Schans ◽  
...  
Keyword(s):  
Psychometric Properties ◽  
Nursing Care ◽  
Latent Trait ◽  
Psychometric Evaluation ◽  
Partial Credit Model ◽  
Partial Credit ◽  
Cross Sectional ◽  
Online Application ◽  
Generalized Partial Credit Model ◽  
Generalized Partial Credit

The instrument called Families Importance in Nursing Care–Nurses’ Attitudes (FINC-NA) is used to measure nurses’ attitudes toward involving families in their nursing care. The aim of this study is to evaluate the FINC-NA scale in a population of Dutch nurses and add new psychometric information to existing knowledge about this instrument. Using a cross-sectional design, 1,211 nurses received an online application in 2015. Psychometric properties were based on polychoric correlations and the Generalized Partial Credit Model. A total of 597 (49%) nurses responded to the online application. Results confirmed a four-subscale structure. All response categories were utilized, although some ceiling effects occurred. Most items increase monotonically, and the majority of items discriminate well between different latent trait scores of nurses with some items providing more information than others. This study reports the psychometric properties of the Dutch language FINC-NA instrument. New insights into the construct and content of items enable the possibility of a more generic instrument that could be valid across several cultures.

scholarly journals Development and Validation of a Novel Knee-Specific Patient-Reported Outcomes Measure

2020 ◽  
pp. 1-11
Author(s):  
James L. Farnsworth ◽  
Todd Evans ◽  
Helen Binkley ◽  
Minsoo Kang
Keyword(s):  
Outcome Measures ◽  
Patient Reported Outcomes ◽  
Patient Reported Outcome Measures ◽  
Patient Reported Outcome ◽  
Measurement Properties ◽  
Partial Credit Model ◽  
Partial Credit ◽  
Specific Patient ◽  
Patient Reported ◽  
Full Study

Context: Previous research suggests that several knee-specific patient-reported outcome measures have poor measurement properties. The patient-reported outcomes knee assessment tool (PROKAT) was created to improve assessment of knee-specific function. Examination of the measurement properties of this new measure is critical to determine its clinical value. Objective: Examine the measurement properties of the PROKAT. Design: Cross-sectional study. Setting: Clinical athletic training setting. Patients or Other Participants: The pilot study included 32 student-athletes (mean age = 20.78 [1.01], males = 56.30%). The full study included 203 student-athletes (mean age = 21.46 [4.64], males = 54.70%) from 3 separate institutions. The participants were recruited for both the pilot and full study using face-to-face and electronic (eg, email and social media sites) communications. Intervention(s): Evaluation of the measurement properties of the PROKAT occurred using the Rasch partial-credit model. Main Outcome Measures: Infit and outfit statistics, item step difficulties, person ability parameters, category function, item and test information functions, and Cronbach alpha. An independent samples t test was used to evaluate the differences in injured and noninjured athletes’ scores. Results: The Rasch partial-credit model analysis of pilot test items and qualitative participant feedback were used to modify the initial PROKAT. Evaluation of the revised PROKAT (32 items) indicated 27 items had acceptable model–data fit. The injured athletes scored significantly worse than the noninjured athletes (t188 = 12.89; P < .01). The ceiling effects for the PROKAT were minimal (3.9%). Conclusions: A major advantage of this study was the use of the Rasch measurement and the targeted population. Compared with alternative knee-specific patient-reported outcome measures (eg, Knee Injury Osteoarthritis Outcome Score, International Knee Documentation Committee Subjective Knee Form), the PROKAT has low ceiling effects in athletic populations. In addition, evidence suggests the measure may be capable of distinguishing between injured and noninjured athletes.

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