scholarly journals The Performance of the Semigeneralized Partial Credit Model for Handling Item-Level Missingness

2020 ◽  
Vol 80 (6) ◽  
pp. 1196-1215
Author(s):  
Sherry Zhou ◽  
Anne Corinne Huggins-Manley
Keyword(s):  
Item Response ◽  
Likelihood Estimation ◽  
Partial Credit Model ◽  
Partial Credit ◽  
Generalized Partial Credit Model ◽  
Full Information Maximum Likelihood ◽  
Response Data ◽  
Item Level ◽  
Generalized Partial Credit ◽  
Item Data

The semi-generalized partial credit model (Semi-GPCM) has been proposed as a unidimensional modeling method for handling not applicable scale responses and neutral scale responses, and it has been suggested that the model may be of use in handling missing data in scale items. The purpose of this study is to evaluate the ability of the unidimensional Semi-GPCM to aid in the recovery of person parameters from item response data in the presence of item-level missingness, and to compare the performance of the model with two other proposed methods for handling such missingness: a multidimensional modeling approach for missingness and full information maximum likelihood estimation. The results indicate that the Semi-GPCM performs acceptably in an absolute sense when less than 30% of the item data is missing but does not outperform the other two methods under any particular conditions. We conclude with a discussion about when practitioners may or may not want to use the Semi-GPCM to recover person parameters from item response data with missingness.

Entwicklungsschritte für einen computeradaptiven Test zur Erfassung von Angst (A-CAT1)

Diagnostica ◽  
2005 ◽  
Vol 51 (2) ◽  
pp. 88-100 ◽  
Author(s):  
Otto B. Walter ◽  
Janine Becker ◽  
Herbert Fliege ◽  
Jakob Bjorner ◽  
Mark Kosinski ◽  
...  
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Partial Credit Model ◽  
Partial Credit ◽  
Response Theory ◽  
Generalized Partial Credit Model ◽  
Generalized Partial Credit

Zusammenfassung. Die empirische Erfassung psychischer Merkmale erfolgt in der Regel mit Instrumenten, die auf der Grundlage der klassischen Testtheorie entwickelt wurden. Seit den 60er Jahren bietet sich hierzu mit der Item Response Theory (IRT) eine Alternative an, die verschiedene Vorteile verspricht. Auf ihrer Grundlage können u.a. computeradaptive Tests (CATs) entwickelt werden, welche die Auswahl der vorgelegten Items dem Antwortverhalten der Patienten anpassen und damit eine höhere Messgenauigkeit bei reduzierter Itemzahl ermöglichen sollen. Wir haben verschiedene Schritte zur Entwicklung eines CAT zur Erfassung von Angst unternommen, um zu prüfen, ob sich die theoretischen Vorzüge der IRT auch in der praktischen Umsetzung bestätigen lassen. In dem vorliegenden Beitrag wird die Entwicklung der zu Grunde liegenden Itembank dargestellt. Hierfür wurde auf Daten von N = 2348 Patienten zurückgegriffen, die an der Medizinischen Klinik mit Schwerpunkt Psychosomatik der Charité zwischen 1995 und 2001 im Rahmen der Routinediagnostik ein umfangreiches Set etablierter konventioneller Fragebögen computergestützt beantwortet hatten. Diese beinhalteten 81 Items, die in einem Expertenrating für das Merkmal Angst als relevant angesehen wurden. Die Eigenschaften dieser Items wurden anhand ihrer residualen Korrelationen nach konfirmatorischer Faktorenanalyse (MplusTM), ihrer Antwortkategorienfunktion (TestgrafTM) und ihrer Diskriminationsfähigkeit (ParscaleTM) überprüft. Es verblieben 50 Items, die für die Anwendung eines polytomen Zwei-Parameter-Modells (Generalized-Partial-Credit-Model) als geeignet angesehen werden können. Orientiert man sich an einer Reliabilität von ρ ≥ .90 und legt für den computeradaptiven Testalgorithmus einen Standardfehler von ≤ .32 fest, so zeigen Simulationsstudien, dass die Merkmalsausprägung für Angst im Bereich von ± 2 Standardabweichungen um den Mittelwert der Stichprobe mit ca. 7 Items ermittelt werden kann. Zudem legen die Simulationsstudien nahe, dass der CAT-Algorithmus das Merkmal in den oberen und unteren Ausprägungen besser zu differenzieren vermag als die konventionell berechnete Summen-Skala des STAI (State).

scholarly journals Contribuições ao estudo do Modelo de Crédito Parcial Generalizado

2017 ◽  
Vol 28 (67) ◽  
pp. 236
Author(s):  
Eduardo Vargas Ferreira ◽  
Caio Lucidius Naberezny Azevedo
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Model Parameters ◽  
Partial Credit Model ◽  
Partial Credit ◽  
Response Theory ◽  
Generalized Partial Credit Model ◽  
Irt Models ◽  
Palabras Clave ◽  
Generalized Partial Credit

<p>Este artigo aborda os mais importantes aspectos inferenciais do Modelo de Crédito Parcial Generalizado (MCPG), da Teoria da Resposta ao Item (TRI). É mostrado um estudo sobre uma das principais dificuldades encontradas no processo de estimação e inferência dos modelos da TRI, que é a falta de identificabilidade. Além disso, apresenta-se a interpretação dos parâmetros do modelo e da função de informação do item e do teste.</p><p><strong>Palavras-chave:</strong> Teoria da Resposta ao Item; Modelos Politômicos; Modelo de Crédito Parcial Generalizado; Psicometria.</p><p> </p><p><strong>Contribuciones al estudio del Modelo de Crédito Parcial Generalizado</strong></p><p>Este artículo aborda los más importantes aspectos inferenciales del Modelo de Crédito Parcial Generalizado (MCPG), de la Teoría de la Respuesta al Ítem (TRI). Se presenta un estudio sobre una de las principales dificultades encontradas en el proceso de estimación e inferencia de los modelos de la TRI, que es la falta de identificabilidad. Por otra parte, se expone la interpretación de los parámetros del modelo y de la función de información del ítem y el test.</p><p><strong>Palabras clave:</strong> Teoría de la Respuesta al Ítem; Modelos Politómicos; Modelo de Crédito Parcial Generalizado; Psicometría.</p><p> </p><p><strong>Contributions to the study of Generalized Partial Credit Model</strong></p><p>This article covers the most important inferential aspects of the Generalized Partial Credit Model (GPCM) of the Item Response Theory (IRT). It presents a study on one of the main difficulties encountered in the process of estimation and inference of the IRT models, which is the lack of identifiability. In addition, it presents the interpretation of the model parameters and the information function of the item and the test.</p><p><strong>Keywords:</strong> Item Response Theory; Polytomous Models; Generalized Partial Credit Model; Psychometrics.</p>

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 Extreme Response Style: A Simulation Study Comparison of Three Multidimensional Item Response Models

2018 ◽  
Vol 43 (4) ◽  
pp. 322-335 ◽  
Author(s):  
Brian C. Leventhal
Keyword(s):  
Item Response ◽  
Partial Credit Model ◽  
Response Model ◽  
Multidimensional Item Response ◽  
Generalized Partial Credit Model ◽  
Response Models ◽  
Item Response Models ◽  
Nominal Response Model ◽  
Extreme Response ◽  
Generalized Partial Credit

Several multidimensional item response models have been proposed for survey responses affected by response styles. Through simulation, this study compares three models designed to account for extreme response tendencies: the IRTree Model, the multidimensional nominal response model, and the modified generalized partial credit model. The modified generalized partial credit model results in the lowest item mean squared error (MSE) across simulation conditions of sample size (500, 1,000), survey length (10, 20), and number of response options (4, 6). The multidimensional nominal response model is equally suitable for surveys measuring one substantive trait using responses to 10 four-option, forced-choice Likert-type items. Based on data validation, comparison of item MSE, and posterior predictive model checking, the IRTree Model is hypothesized to account for additional sources of construct-irrelevant variance.

scholarly journals Psychopathy Checklist: Youth Version psychometric properties in an Item Response Theory polytomous model

2020 ◽  
Vol 37 ◽  
Author(s):  
Raul Corrêa Ferraz ◽  
Fernando de Jesus Moreira Junior ◽  
Fernanda de Vargas ◽  
Fernanda Xavier Hoffmeister ◽  
Gabriel José Chittó Gauer ◽  
...  
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Latent Trait ◽  
Partial Credit Model ◽  
Theory Approach ◽  
Response Theory ◽  
Generalized Partial Credit Model ◽  
Affective Characteristics ◽  
Psychopathy Checklist ◽  
Generalized Partial Credit

Abstract This study assessed the applicability of the Psychopathy Checklist: Youth Version in a sample of teenagers confined in socio-educational institutions. Using an Item Response Theory approach, item properties of this instrument were reviewed using the generalized partial credit model. Eight of the original twenty items of the original instrument were discarded due to low discrimination parameters. As expected, the most discriminating items in the assessment of psychiatric traits were those which affective characteristics are more typical in the description of psychopathic traits, and their larger variability among juveniles is reflected in the checklist’s answers. Item anchoring, in turn, determined five anchor levels. Conclusions based on the results are twofold: (a) a shorter version of this measure can offer the same level of information obtained from the full instrument and (b) the measure provides more information on average latent trait levels and is inadequate for clinical use.

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