scholarly journals Analysis of the Ruff 2 & 7 Test of Attention with the Rasch Poisson Counts Model

2019 ◽  
Vol 12 (1) ◽  
pp. 7-11
Author(s):  
Mahsa Nadri ◽  
Purya Baghaei ◽  
Zahra Zohoorian
Keyword(s):  
Item Response ◽  
Rasch Model ◽  
Internal Validity ◽  
Measurement Model ◽  
Cognitive Tasks ◽  
Theory Analysis ◽  
Item Response Theory Analysis ◽  
The Individual ◽  
The Rasch Model ◽  
Poisson Counts

Background:Attention is a basic neurocognitive function which is a prerequisite for performance on more complex cognitive tasks. The Ruff 2 & 7 test is a well-known measure of attention with a well-supported theoretical and empirical underpinnings.Objective:The Ruff 2 & 7 test, has not been subjected to rigorous item response theory analysis yet. The purpose of this research was to examine the fit of the Ruff 2 & 7 test to the Rasch Poisson Counts Model (RPCM).Methods:Responses of 138 nonclinical subjects to the Ruff 2 & 7 test were analyzed with the RPCM measurement model using ‘lme4’ package in R. The fit of the individual items (blocks) and the overall test to the model were examined.Results:Findings showed that three out of seven scoring techniques fit the Rasch model. The scoring techniques which fitted the model were total number of characters cancelled, total number of characters correctly cancelled, and total number of characters correctly cancelled minus errors of commission.Conclusion:Three of the scoring techniques fit the RPCM which support the internal validity of the test when these scoring procedures were employed. Therefore, the Ruff 2 & 7 test is psychometrically uni-dimensional when these three scores are computed.

Introduction to bifactor polytomous item response theory analysis

2017 ◽  
Vol 60 ◽  
pp. 41-63 ◽  
Author(s):  
Michael D. Toland ◽  
Isabella Sulis ◽  
Francesca Giambona ◽  
Mariano Porcu ◽  
Jonathan M. Campbell
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Response Theory ◽  
Theory Analysis ◽  
Polytomous Item ◽  
Item Response Theory Analysis ◽  
Polytomous Item Response Theory ◽  
Polytomous Item Response

scholarly journals Development and Validation of the Yonsei Lifestyle Profile-Satisfaction (YLP-S) Using the Rasch Measurement Model

2021 ◽  
Vol 58 ◽  
pp. 004695802110176
Author(s):  
Kang-Hyun Park ◽  
Ickpyo Hong ◽  
Ji-Hyuk Park
Keyword(s):  
Older Adults ◽  
Rasch Analysis ◽  
Age Groups ◽  
Internal Validity ◽  
Measurement Model ◽  
Limited Evidence ◽  
Fit Statistics ◽  
Item Functioning ◽  
Development And Validation ◽  
The Rasch Model

Lifestyle plays an important role in determining health and vitality among older adults. However, there is limited evidence regarding lifestyle assessment. This study examined the psychometric properties of the Yonsei Lifestyle Profile-Satisfaction (YLP-S). The participants in the study included 156 older adults. Rasch analysis was used to test unidimensionality, fit statistics, and the precision of the YLP-S. The YLP-S demonstrated a unidimensional measurement construct, and 18 items fit the Rasch model. The YLP-S illustrated reasonable precision (person strata = 5.37). Only 4 items showed differential item functioning by sex or age groups. The findings indicate that the YLP-S demonstrated sound internal validity and can be used by health professionals to measure the multifaceted lifestyle of older adults.

scholarly journals Investigating diagnostic bias in autism spectrum conditions: An item response theory analysis of sex bias in the AQ-10

2016 ◽  
Vol 10 (5) ◽  
pp. 790-800 ◽  
Author(s):  
Aja Louise Murray ◽  
Carrie Allison ◽  
Paula L. Smith ◽  
Simon Baron-Cohen ◽  
Tom Booth ◽  
...  
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Autism Spectrum ◽  
Autism Spectrum Conditions ◽  
Sex Bias ◽  
Response Theory ◽  
Theory Analysis ◽  
Diagnostic Bias ◽  
Item Response Theory Analysis

scholarly journals Controlling response dependence in the measurement of change using the Rasch model

2017 ◽  
Vol 27 (12) ◽  
pp. 3709-3725 ◽  
Author(s):  
David Andrich
Keyword(s):  
Rasch Model ◽  
Real Data ◽  
Repeated Measurements ◽  
Measurement Of Change ◽  
Location Parameters ◽  
Response Dependence ◽  
The Individual ◽  
First Time ◽  
The Rasch Model ◽  
Research And Policy

The advantages of using person location estimates from the Rasch model over raw scores for the measurement of change using a common test include the linearization of scores and the automatic handling of statistical properties of repeated measurements. However, the application of the model requires that the responses to the items are statistically independent in the sense that the specific responses to the items on the first time of testing do not affect the responses at a second time. This requirement implies that the responses to the items at both times of assessment are governed only by the invariant location parameters of the items at the two times of testing and the location parameters of each person each time. A specific form of dependence that is pertinent when the same items are used is when the observed response to an item at the second time of testing is affected by the response to the same item at the first time, a form of dependence which has been referred to as response dependence. This paper presents the logic of applying the Rasch model to quantify, control and remove the effect of response dependence in the measurement of change when the same items are used on two occasions. The logic is illustrated with four sets of simulation studies with dichotomous items and with a small example of real data. It is shown that the presence of response dependence can reduce the evidence of change, a reduction which may impact interpretations at the individual, research, and policy levels.

Sign in / Sign up

Export Citation Format

Share Document