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Human Scoring with Automated Scoring in Mind
Published in Duanli Yan, André A. Rupp, Peter W. Foltz, Handbook of Automated Scoring, 2020
Psychometrics is a field that focuses on applications of statistical methods to the measurement of psychological phenomena, and AS teams should be aware of the extensive body of research that focuses on the development and application of measurement models to ratings (e.g., true score test theory, generalizability theory, item response theory, Rasch measurement, signal detection theory). Yan and Bridgeman (Chapter 16, this handbook) discuss the statistical models for AS systems. Within each of these approaches to scaling rating data, researchers have sought to evaluate the accuracy with which rater effects influence decisions that are made about raters and examinees, the sensitivity of indices that are used to detect rater effects, and the relative worth of these varying approaches to measuring raters and rater effects.
Involving older adults in design research
Published in Sara J. Czaja, Walter R. Boot, Neil Charness, Wendy A. Rogers, Designing for Older Adults, 2019
Sara J. Czaja, Walter R. Boot, Neil Charness, Wendy A. Rogers
With respect to psychometrics, two important constructs are reliability (stability or consistency of a measure) and validity (measures assess what is intended to be measured). There are various types of reliability and validity, the discussion of which is beyond the scope of this handbook. The sensitivity (the degree that a measure detects the presence of a characteristic in someone with the characteristic – e.g., high blood pressure) and specificity of a measure (the likelihood that a measure will detect the absence of a characteristic in someone without the characteristic) are also important considerations. Other issues to consider include participant burden, feasibility, cost, and available data collection equipment and data analysis resources.
Assessing Psychometric Scale Properties of Patient Safety Culture
Published in Patrick Waterson, Patient Safety Culture, 2018
Jeanette Jackson, Theresa Kline
This chapter provides an overview of the psychometric properties of the HSOPSC using both classical test theory (CTT) and the modern approach, often referred to as Item Response Theory (IRT). To enhance the understanding and importance of IRT, the basic principles will first be introduced. In particular, three fundamental outcomes of the IRT approach will be highlighted: (1) item characteristic curves, (2) measurement information, and (3) invariance. Moreover, this chapter will present data that have been previously analysed and published, using the classical approaches of exploratory and confirmatory factor analysis by Waterson and colleagues (2010) in order to contrast and discuss IRT results with findings based on the factor analytical approach. Finally, practical implications will be highlighted to encourage future healthcare research and healthcare service evaluations to apply and implement IRT findings when measuring patient safety culture.
Customer satisfaction of bicycle sharing: studying perceived service quality with SEM model
Published in International Journal of Logistics Research and Applications, 2019
Zhiying Zhou, Zuopeng (Justin) Zhang
The consistency in the questionnaire responses reflects the relationship between the various parameters under investigation and it can be used to determine whether the same contents have been obtained in each investigation. The most widely used consistency index is the reliability coefficient Cronbach’s α, defined as a (lower bound) estimate of the reliability of a psychometric test used for tau-equivalent reliability (Cronbach,1951). The greater the value of Cronbach’s α, the more reliable the data is (Zhang 2017). It is a common practice to deem data to be reliable when Cronbach’s α value is above 0.6 (Shi 2013). Table 3 shows the Cronbach’s α values obtained from the survey of this study. The overall Cronbach’s α value is 0.916, much higher than the 0.6 reliability criteria. Furthermore, Cronbach’s α values for all latent variables are in the range of 0.627–0.813, indicating that the data from this survey is reliable.
Temporal relationship between attitude toward mathematics and mathematics achievement
Published in International Journal of Mathematical Education in Science and Technology, 2022
Henry Nsubuga Kiwanuka, Jan Van Damme, Wim Van den Noortgate, Chandra Reynolds
MA was measured by three mathematics tests administered to grade 7 students at the beginning, half-way and end of school year 2012. The tests were designed to measure numeration, algebra, fractions, geometry and word problems, assessing the same domain. Each test item was scored 1 in case of a correct response or 0 in case of a wrong response. The raw scores of the tests were analyzed using Item Response Theory (IRT), in order to estimate the proficiency of the students and study the psychometric quality of the items. To link the tests to each other, we combined the data from our group (4,819 students) with those of another group (720 students from another study who answered part of the items of all three tests). The two-parameter logistic IRT model was used to estimate the difficulty and discrimination parameters with computer program BILOG-MG (Zimowski et al., 1996). The study of the item quality resulted in a reduction of the items. Out of 103 items, one item was removed because it did not correlate with the other items, eight items were removed because of too low or too high difficulty estimates and very poor discrimination estimates. The 94 good items were calibrated to create a common IRT metric scale so that the tests were comparable across the three measurement points. No subscales were computed because of the limited number of items for some subscales. The student proficiency estimates (which will be referred to later as IRT scores) at the first time point were scaled to a mean of 50 and a standard deviation of 10 using T-transformation, and this scale was used as the base achievement at the subsequent time points.
Judging the Scientific Quality of Applied Lighting Research
Published in LEUKOS, 2019
Jennifer A. Veitch, Steve A. Fotios, Kevin W. Houser
Using multiple methods (i.e., converging operations) to measure the target concepts builds a strong knowledge base because every behavioral measurement has error, but each method and each tool tends to err in different ways. Psychometrics is a subdiscipline of psychology that concerns the development of measurement instruments with which to assess intangible concepts, called constructs—for example, “preferred lighting conditions” is a construct, as is “knowledge about photometry.” Instructors who set examination questions are performing psychometry, although they might be unlikely formally to apply its standards (American Educational Research Association, the American Psychological Association, and the National Council on Measurement in Education 2014).