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Symmetry considerations are important in science, and Group Theory is a theory of symmetry. Classical Measurement Theory is the most used measurement theory in the social and behavioral sciences. In this article, the author uses Matrix Lie (Lee) group theory to formulate a measurement model. Symmetry is defined and illustrated using symmetries of the square. Then it is shown how a matrix group can represent the symmetries of the square. A brief introduction to Group Theory follows. Then four assumptions on which the Lie matrix group model of measurement is based are articulated. Formulation of the model follows. The notion of approximate symmetry is introduced, and a measure of approximate symmetry is proposed. It is shown CMT is a special case of the Lie matrix group model. A simulation is used to test invariances predicted from the Lie matrix group model. Finally, implications of this model are considered. [ABSTRACT FROM AUTHOR]

Background The quality of life of patients with nephrotic syndrome requires a lot of focus, and improvements. A relevant scale can be used to measure it, but there is no nephrotic syndrome-specific quality of scale. Objective To develop a Quality of Life Instruments for Chronic Diseases-Nephrotic Syndrome〔QLICD-NS (V2.0) 〕 combined with QLICD-GM (V2.0), then verify it using the classical test theory. Methods From 2017 to 2021, an item pool was established according to literature review and the results of a semi-structured questionnaire, then the items were screened in accordance with a pre-test and importance score rated by physicians and patients, after that, the draft of the QLICD-NS (V2.0) was developed. The draft version was tested using onsite interview and questionnaire survey in nephrotic syndrome patients treated in Department of Nephrology, the Affiliated Hospital of Guangdong Medical University from March to November 2021. The first measurement was conducted on the day of admission, the second measurement was conducted with some of the patients, and the third measurement was conducted on the day of discharge. The coefficient of variation, correlation coefficient and Cronbach's α, factor analysis and classical test theory were used to evaluate QLICD-NS (V2.0) . Results The QLICD-NS (V2.0) contains 15 items, belonging to three domains of clinical symptoms, adverse drug reactions and psychological effects. The Cronbach's α measuring the split-half reliability was greater than 0.7 for the scale and each of the three domains. With the Chinese version of SF-36 as the calibration standard, the domains of the QLICD-NS (V2.0) were highly correlated with their counterpart domains of the Chinese version of SF-36. The standardized response mean was greater than 0.80 for all domains and items (except for the cognition and social support items), indicating that the responsiveness of the QLICD-NS (V2.0) was good. Scanning the QR code in the text can obtain the detailed evaluation of the scale. Conclusion The QLICD-NS (V2.0) compiled by us includes 15 items, and has proven with good reliability, validity and responsiveness.

Objectives: This article is designed for comparison and contrast of item response theory measurement with classical measurement theory (Classical Measurement Theory) as well as to determine the various advantages offered by item response theory in the setting of medical education. Summary: Classical measurement theory is being impartial and inherent, is used more often than other models in medical education. However, there is one restriction encountered in the use of classical measurement theory that is it sample dependent and the data is bewildered in the specified sample that the researcher has assessed. Whereas, the score in item response theory separate from the sample or stimuli of assessment. Item Response Theory is consistent, it allows for easy evaluation of examination scores enabling the score to be placed in constant measurement scale and compare the change in students' ability with time. There are various models of Item Response Theory out of which three are discussed along with their statistical assumptions. Conclusions: Item Response Theory being a capable tool is able to simplify a major issue of Classical Measurement Theory, i.e. bewilderment of skill of examinee with item characteristics. The Item Response Theory measurement inscribes the problems in medical education like removing rater mistakes from evaluation. [ABSTRACT FROM AUTHOR]

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Introduction: Previous research had shown the suitability of several questionnaires predicting the obstructive sleep apnea syndrome. Measurement properties of an online screening questionnaire were studied. Methods: The sample consisted of 184 Portuguese adults (89 men and 95 women); 46 of them were polysomnographically diagnosed with the untreated obstructive sleep apnea syndrome. The participants were assessed with an online questionnaire of sleep apnea risk, from University of Maryland. Results: A principal component factor analysis was performed, revealing a single factor (49.24% of the total variance). Internal consistency was minimally adequate (α=0.74). The mean of inter-item correlation was of 0.35 (0.120.61), whereas the item-total correlations were considered good (0.520.81). The total score for patients was significantly higher than for healthy participants (p0.05). Furthermore, the ability of the measure in discriminating between healthy subjects and OSA subjects was good. Overall data from the Rasch analysis was consistent with the guidelines of Linacre, scores show good model fit and psychometric adequacy. Conclusions: The measure showed an adequate structural, internal and criterion validity, suggesting this as a useful and effective screening for sleep apnea risk in Portuguese adults.

Abstract: The descriptive statistic known as effect size measures the distinguishability of two sets of data. Distingishability is at the core of diagnosis. This article is intended to point out the importance of effect size in the development of effective diagnostics for mild Traumatic Brain Injury and to point out the applicability of the effect size statistic in comparing diagnosic efficiency across the main proposed TBI diagnostic methods: psychological, physiological, biochemical and radiologic. Comparing diagnostic approaches is difficult because different researcher in different fields have different approaches to measuring efficacy. Converting diverse measures to effect sizes, as is done in meta-analysis, is a relatively easy way to make studies comparable.

The descriptive statistic known as "effect size" measures the distinguishability of two sets of data. Distingishability is at the core of diagnosis. This article is intended to point out the importance of effect size in the development of effective diagnostics for mild traumatic brain injury and to point out the applicability of the effect size statistic in comparing diagnostic efficiency across the main proposed TBI diagnostic methods: psychological, physiological, biochemical, and radiologic. Comparing diagnostic approaches is difficult because different researcher in different fields have different approaches to measuring efficacy. Converting diverse measures to effect sizes, as is done in meta-analysis, is a relatively easy way to make studies comparable. [ABSTRACT FROM AUTHOR]