Measures Of Variability Research Articles

On a general theoretical framework of reliability.

Reliability is an essential measure of how closely observed scores represent latent scores (reflecting constructs), assuming some latent variable measurement model. We present a general theoretical framework of reliability, placing emphasis on measuring the association between latent and observed scores. This framework was inspired by McDonald's (Psychometrika, 76, 511) regression framework, which highlighted the coefficient of determination as a measure of reliability. We extend McDonald's (Psychometrika, 76, 511) framework beyond coefficients of determination and introduce four desiderata for reliability measures (estimability, normalization, symmetry, and invariance). We also present theoretical examples to illustrate distinct measures of reliability and report on a numerical study that demonstrates the behaviour of different reliability measures. We conclude with a discussion on the use of reliability coefficients and outline future avenues of research.

Assessing transparency and methodological precision in variable measurement within organizational research: implications for validity

Assessing transparency and methodological precision in variable measurement within organizational research: implications for validity

Effects of traditional Chinese medicine on outcomes and costs of dementia care: results from a retrospective real-world study

ObjectivesThis study aims to assess the impact of Traditional Chinese Medicine (TCM) on dementia patients, utilizing real-world data. Specifically, it seeks to evaluate how TCM influences clinical outcomes by examining changes in the Clinical Dementia Rating (CDR) and Mini-Mental State Examination (MMSE) scores, as well as its effect on medical expenses over a two-year period. Data from a multi-center research database spanning from 2004 to 2021 will be used to achieve these objectives, addressing the current gap in empirical data concerning intuitive outcomes and cognitive function assessments.MethodsPropensity score matching was adopted to improve comparability among the intervention and control groups. Due to repeated dependent variable measurements, the generalized estimating equation was used to control for socio-demographic characteristics, regional characteristics, and Western medicine treatments for dementia.ResultsAfter propensity score matching, a total of 441 research subjects were included: 90 in the TCM intervention group and 351 in the non-TCM intervention group. The results of multivariate regression analysis showed that compared with the non-TCM intervention group, the MMSE scores in the TCM intervention group increased by 0.608 points each year. The annual change in CDR scores in the TCM intervention group was 0.702 times that of the non-TCM utilization group. After TCM intervention, annual outpatient expenses increased by US$492.2, hospitalization expenses increased by US$324.3, and total medical expenses increased by US$815.9, compared with the non-intervention group.ConclusionsTCM interventions significantly decelerate cognitive decline in dementia patients, evidenced by slower reductions in MMSE scores and mitigated increases in CDR scores. However, these benefits are accompanied by increased medical expenses, particularly for outpatient care. Future healthcare strategies should balance the cognitive benefits of TCM with its economic impact, advocating for its inclusion in dementia care protocols.

Bedside imaging

Sonography, in particular echocardiography, is essential in the assessment of volume status and hemodynamics in critically ill patients. Examination of the left ventricle, in addition to assessing ventricular function, provides valuable information, including the "kissing papillary muscle sign," which may indicate fluid responsiveness. Examination of the right ventricle is also important because it is sensitive to both volume and pressure overload. Assessment of diastolic function and measurement of inferior vena cava width and variability provide clues to left and right ventricular preload, respectively. Measurement of stroke volume and cardiac output allows further assessment of hemodynamics and also permits determination of stroke volume variability.

The impact of executive team competency-sharing degree on firm innovation performance

In China’s high-quality development context, the key role of executive teams in corporate innovation is increasingly prominent. However, effectively utilizing the synergistic effect of competencies within these teams to boost innovation performance remains a crucial research issue. A sample of 2,350 companies in Shanghai and Shenzhen A-shares from 2010 to 2022 was used to examine the impact of the executive team’s capability-sharing degree on firm innovation performance. The study indicates that the degree of managerial competence sharing, entrepreneurial competence sharing, and technological competence sharing within the executive team positively impacts firm innovation performance. These findings remain robust in the face of variations in dependent variable measures, lagged independent variables, and the propensity score matching method. Environmental dynamism is identified as playing a positive moderating role in the relationship between the influence of managerial, entrepreneurial, and technological capability-sharing degrees and firm innovation performance. Further analysis of heterogeneity reveals that the impact of the executive team’s capability-sharing degree on firms’ innovation performance varies based on the nature of property rights, firm size, and industry competitiveness. This study, grounded in top-level ladder theory, offers a framework for enhancing team capabilities and overcoming growth obstacles through executive team competence sharing.

12596 Characterizing Glycemic Variability In Novel Subphenotypes Of Individuals At Elevated Risk For Type 2 Diabetes Using Continuous Glucose Monitoring

Abstract Disclosure: A.J. Kretowski: None. P. Konopka: None. A. Janucik: None. A. Citko: None. A. Paszko: None. M. Klak: None. A. Golonko: None. A. Szklaruk: None. L. Szczerbinski: None. Background: The heterogeneity among individuals at elevated risk for Type 2 Diabetes (T2D) recently has led to the identification of six subphenotypes, each with distinct risks for developing T2D, its complications, and mortality. Our study leveraged Continuous Glucose Monitoring (CGM) to offer a detailed characterization of these subphenotypes, aiming to uncover differences in glycemic variability and control. Methods: CGM data from 616 individuals without diabetes, from the Polish Registry of Diabetes (PolReD) study, classified into six clusters, were analyzed. The PolReD used Freestyle Libre 2 (Abbott) as the CGM device. CGM-derived measures of glucose control and glucose variability were calculated using the iglu R package. We utilized Analysis of Variance (ANOVA) and Analysis of Covariance (ANCOVA), adjusting for age and sex, to identify significant differences in CGM parameters across the clusters. Results: Our analysis identified significant differences in several CGM-derived parameters among the clusters, notably in the Glycemic Risk Assessment Diabetes Equation (GRADE), Standard Deviation of weekly glucose values (SDw), Mean Amplitude of Glycemic Excursions (MAGE), Maximum glucose value, Glucose range, and Mean Absolute Glucose (MAG). Clusters 3 and 5, characterized by beta-cell dysfunction and high insulin resistance respectively, and associated with the highest risk of T2D, exhibited the greatest glucose variability, with elevated risk for glycemic excursions. In contrast, Cluster 4, indicative of a metabolically healthy obesity profile with a low risk of T2D, demonstrated the most stable glycemic control and the lowest variability among the clusters. Conclusions: This study shows that subtypes of patients at elevated risk for T2D exhibit distinct patterns in CGM-derived parameters, indicating variations in glucose control and stability that extend beyond traditional fasting and post-challenge glucose assessments. Notably, we found that subtypes facing the highest T2D risk display increased glycemic variability, despite their differing underlying mechanisms of dysglycemia. These findings highlight the utility of CGM as a tool for identifying individuals at an increased risk of T2D, reducing the need for extensive phenotyping typically required for cluster assignment. Presentation: 6/1/2024

Acute Alcohol Consumption and Arrhythmias in Young Adults: The MunichBREW II Study.

and aims: Acute excessive alcohol intake may cause the holiday heart syndrome, characterized by cardiac arrhythmias including atrial fibrillation. Since underlying data are scarce, the study aimed to prospectively investigate the temporal course of occurring cardiac arrhythmias following binge drinking in young adults. A total of 202 volunteers planning acute alcohol consumption with expected peak breath alcohol concentrations (BAC) of ≥1.2 g/kg were enrolled. The study comprised 48-hour electrocardiogram (ECG) monitoring covering baseline (hour 0), 'drinking period' (hours 1-5), 'recovery period' (hours 6-19), and two control periods corresponding to 24 hours after the 'drinking' and 'recovery periods', respectively. Acute alcohol intake was monitored by BAC measurements during the 'drinking period'. ECGs were analyzed for mean heart rate, atrial tachycardia, premature atrial complexes (PAC), premature ventricular complexes (PVC), and heart rate variability (HRV) measures. Data revealed an increase in heart rate and an excess of atrial tachycardias with increasing alcohol intake. HRV analysis indicated an autonomic modulation with sympathetic activation during alcohol consumption and the subsequent 'recovery period', followed by parasympathetic predominance thereafter. PACs occurred significantly more frequently in the 'control periods', whereas PVCs were more frequent in the 'drinking period'. Ten participants experienced notable arrhythmic episodes, including atrial fibrillation and ventricular tachycardias, primarily during the 'recovery period'. The study demonstrates the impact of binge drinking on heart rate alterations and increased atrial tachycardias during 'drinking period', and the occurrence of clinically relevant arrythmias during the 'recovery period', emphasizing the holiday heart syndrome as a health concern.

Pengaruh Brand Image dan Brand Trust Terhadap Brand Loyalty Produk Hand & Body Lotion Citra (Studi Pada Followers Akun Shopee Unilever Beauty Shop)

This research aims to determine and analyze the influence of brand image and brand trust on brand loyalty of Citra hand & body lotion products (Study on followers of the Unilever Beauty Shop shopee account). This research uses a quantitative type of research. Variable measurement in this research uses a Likert scale. The population in this study are followers of the Unilever Beauty Shop Shopee account. The sample taken in this research was 100 people using purposive sampling technique. Data collection in this research used a questionnaire. This research uses SPSS for Windows version 29. The results of the research show that Brand Image and Brand Trust have a significant effect on Brand Loyalty, Brand Image has a significant effect on Brand Loyalty and Brand Trust has a significant effect on Brand Loyalty.

Perilaku Keuangan Menabung Mahasiswa Rantau Fakultas Ekonomi dan Bisnis UPN “Veteran” Jawa Timur

The ability to manage finances effectively is crucial for students living away from home, as they must manage their own budgets while meeting various academic and personal needs. This study aims to analyze the relationship between financial literacy, lifestyle, and financial attitudes toward saving behavior among students of the Faculty of Economics and Business at UPN "Veteran" Jawa Timur who live away from home. The research employs a quantitative approach with variable measurement using a Likert scale. The sampling technique used is purposive sampling, involving 98 respondents. Hypotheses were tested using SmartPLS software. The results show that financial literacy contributes to saving behavior decisions among students of the Faculty of Economics and Business at UPN "Veteran" Jawa Timur, lifestyle contributes to saving behavior decisions, and financial attitudes also contribute to saving behavior decisions among these students.

Worst-case distortion riskmetrics and weighted entropy with partial information

In this paper, we discuss the worst-case distortion riskmetrics for general distributions when only partial information (mean and variance) is known. This result is applicable to a general class of distortion risk measures and variability measures. Furthermore, we also consider the worst-case weighted entropy for general distributions when only partial information is available. Specifically, we provide some applications for entropies, weighted entropies and risk measures. The commonly used entropies include Gini functional, cumulative residual entropy, tail-Gini functional, cumulative Tsallis past entropy, extended Gini coefficient, among others. The risk measures contain some premium principles and shortfalls based on entropy. The shortfalls include the Gini shortfall, extended Gini shortfall, shortfall of cumulative residual entropy and shortfall of cumulative residual Tsallis entropy with order α.

Measurements of temporal variability of acoustic scattering from the seafloor in shallow-water sandy sites.

In the ocean, the performance of active sonar systems depends on the acoustic properties of the seafloor. Daily to monthly variations in near-bottom hydrodynamics and benthic biological activity may affect seafloor properties which then influence the acoustic response of the seafloor. The dependence of seafloor scatter on evolving environmental parameters was investigated using high-frequency active acoustic systems. Seafloor scattering measurements were analyzed in a series of experiments (two weeks to five months in duration) from downward-looking sonars oriented at 20° grazing angle with respect to the seafloor. Data were obtained in two shallow water locations near Portsmouth, New Hampshire, USA: a wave-dominated site and a site dominated by tidal currents. The bottom type for both sites was gravelly sand. The experimental set-up consisted of a tripod placed on the seafloor equipped with three transducers operating at 38, 70, and 200 kHz, a wave-sensing CTD, and underwater cameras. Scattering strength time series were obtained taking into account the local seafloor slope. Results show that there is variability in scattering strength (both in mean levels and distributions). Large variations often coincided with storm events, suggesting that this variability may be driven by changes in bottom roughness caused by storm-related hydrodynamics.

Effects of a sedentary behaviour intervention in emergency dispatch centre phone operators: a study protocol for the SECODIS randomised controlled cross-over trial

IntroductionSedentary behaviour is a public health problem. We mainly have sedentary behaviour at work, transforming them into occupational risk. To our knowledge, there is no intervention study on the reduction...

The repeatability of stride time variability, regularity, and long-range correlations

BackgroundDetrended fluctuation analysis (DFA) and sample entropy (SE) measure the long-term correlations and regularity of gait patterns, respectively, having previously been used to identify participants at risk of falling, previous history of injury, or patients with motor diseases. Since these measures are more sensitive to gait impairment than linear measures (e.g., the standard deviation [SD] of stride time), they can be potentially used in military medicine to identify soldiers at risk of injury. However, clinometric properties are yet to be established. Research QuestionWhat is the repeatability of DFA, SE, and traditional linear measures of stride time variability (SD and coefficient of variation [CV]) under various load and speed constraints? MethodsFourteen Australian Army trainee soldiers (age: 25.6 ± 5.9 y, height: 1.74 ± 0.08 m, body mass: 77.2 ± 15.1 kg, service: 1.5 ± 1.8 y) attended three sessions over two weeks, completing four 12-minute walking trials on an instrumented treadmill in each session. Participants walked with a combination of 0 kg or 23 kg loads at a self-selected or 5.5 km/h speed. Heel contacts from the right foot were identified using treadmill-embedded force plates. From 512 stride time intervals, linear (SD and CV), and non-linear (DFA and SE) measures were obtained. To assess the between-session repeatability, intraclass correlations (ICC 2,1) were employed. Results and SignificanceThere was poor-to-moderate repeatability for the SD (ICC: 0.357–0.545) and CV (ICC: 0.371–0.529). DFA showed poor-to-moderate repeatability (ICC: 0.013–0.504), while SE had poor repeatability (ICC: 0.133–0.226). Previous studies have shown that differences of > 0.19 in DFA and > 0.66 in SE can differentiate between healthy and pathological gait. These values are greater than this study's reported standard error of measurement, indicating that clinically meaningful changes may still be detectable despite low repeatability.

Development of a web-based ecological momentary assessment tool to measure day-to-day variability of the symptoms in patients with Sjögren’s disease

ObjectivesTo develop and validate a web-based ecological momentary assessment (EMA) tool to enhance symptoms monitoring among patients with Sjögren’s disease (SjD).MethodsConsecutive adults with SjD were enrolled in this pilot observational...

Ambivalent effects of mass cultivation of biodiesel producible green alga Tetraselmis striata on a microbial ecosystem: Evidence from mesocosm experiments

A 280-ton plant for the mass cultivation of Tetraselmis striata was operated from 2012 to 2019 to produce biodiesel fuel in western Korean coastal waters (Incheon) as a pilot project. This was the first instance globally where a microalgal mass cultivation plant for biodiesel production was implemented in coastal waters, and no prior studies had investigated the impact of microalgal mass cultivation plant on surrounding microecosystems. In this study, bioreactors (1× and 10×) mimicking a large-scale T. striata cultivation plant were installed in semi-permeable a mesocosms (5 tons) to assess their impact on the microbial ecosystem. The results showed that the release of large amounts of dissolve organic carbon (DOC) from the T. striata bioreactors. The 10× pond had a DOC concentration of 21.3 mg/L compared to the control pond of 2.1 mg/L. For the Water Quality Index (WQI), the 1× and 10× bioreactor installed mesocosms improved from Class II (Good) at the beginning of the experiment to Class I (Excellent) via decreasing nutrient levels and increasing of DO levels. However, from a biodiversity perspective, the microbial ecosystem deteriorated, with reductions in the diversity of zooplankton, ciliates, and phytoplankton. The correlation analysis and random forest variable importance measures indicated that the primary factor driving these changes was the alteration of the bacterial community due to elevated DOC levels. These findings indicate that while the mass cultivation of T. striata may improve physicochemical water quality, it has adverse effects on biological environments. Therefore, it is crucial to monitor physical, chemical, and biological factors comprehensively when cultivating microalgae on a large scale in marine environments.

Estimation on powdery mildew of wheat canopy based on in-situ hyperspectral responses and characteristic wavelengths optimization

Wheat powdery mildew (WPM) mainly damages leaves, which leads to yield reduction. Although spectroscopy has been considered as one of the effective methods to detect crop diseases, the severity estimation of WPM is challenged by complex changes of wheat canopy reflection, wavelength redundancy in hyperspectral data, et al., so that to reduce the accuracy of disease index (DI) estimation. Aiming to estimate DI of WPM, an optimization method combined of band intervals and sensitive wavelengths screening was proposed by in-situ reflected spectral responses. Field experiments were conducted in 2022 and 2023. With regards to data processing, after preprocessing by Savitzky-Golay (SG) and multiplicative scatter correction (MSC) methods, the backward interval partial least squares (Bipls) method was used to featuring band interval. Then, the characteristic wavelengths in the selected interval were optimized by the variable important in projection (VIP), maximal information coefficient (MIC) and variable importance measure based on random forest (RFVIM) method, separately. Finally, partial least squares regression (PLSR) was used to establish the DI estimating model of WPM, and the best model was selected by comparing the performance among the models. The results indicate that the Bipls-VIP-PLSR model has the best performance (2022: =0.78, RMSEV =10.94%; 2023: =0.75, RMSEV=11.73%), and it was used to estimate the DI changes in the field. The distribution map of DI provided a potential for WPM monitoring and plant protection decision-making.

Machine learning ellipsometry as a sensitive diagnostic tool to study reproductive biology in Zika virus infected murine models

Machine-learning spectroscopy is a recent scientific and fast-growing area where specific machine-learning solutions are used to process spectroscopic data beyond traditional physical modeling. Here, several machine learning models are optimized and trained for processing highly sensitive broadband variable angle spectroscopic ellipsometry measurements as a new tool in reproductive biology. This new method is applied to classify semen samples obtained from male offspring from ZIKV-infected and uninfected murine models. The method is label-free, cost-effective, simple, and reaches excellent performance. The combination of spectroscopic depolarization degree data with a well-optimized and trained SVM model resulted in the excellent performance of AUROC = 0.99, accuracy = 92%, specificity = 87% and sensibility = 97%. Optical modeling of ellipsometry spectra with Kramers–Kronigconsistent B-splines that takes care of incoherent reflections in the samples allowed for the extraction of the average semen sample refraction index for each class, revealing small differences that were attributed to the observed semen head defects, protamination failure, and DNA fragmentation.

Green governance and stock price crash risk: Evidence from China

This study examines whether and how green governance affects stock price crash risk using a large sample of Chinese listed firms from 2010 to 2021. The results show that stock price crash risk is negatively affected by corporate green governance level. Cross-sectional analyses suggest that the decreasing impact of green governance on crash risk is more pronounced for firms with weak external supervision, high risk-taking degree, fewer female directors, and facing stronger environmental regulation. Moreover, information transparency and corporate reputation are two underlying channels through which green governance impacts crash risk. Our findings also hold after several robustness checks including sample intervals change, and alternative variable measurement, propensity score matching, instrumental variables, and Heckman two-step method.

Decreased ventricular repolarization variability in one-year-olds of gestational diabetes mothers

BackgroundGestational diabetes mellitus (GDM) is currently the most common medical complication in pregnancy, affecting approximately 13 % of all pregnant women. Although long-term effects on the offspring are still unclear, previous studies indicate ventricular myocardial changes. ObjectivesThe aim of our study was to investigate whether early biomarkers such as QT interval variability (QTV) are sensitive enough to predict these structural changes in children of GDM mothers. MethodsWe focused on children of GDM mothers. Healthy children of mothers without GDM served as controls. All of them were examined at the German Heart Center, Munich, Germany. Heart rate variability (HRV) and QTV measures were extracted from 10 to 15 min Einthoven II electrocardiograms, split into 5 min windows, to characterize the effects of possible autonomic nervous system alterations and cellular ventricular mutations. Results75 children were included in this prospective observational case-control study; 42 of them were children of GDM mothers. The median age at the examination was 12 months (11–13 months). We found decreased QTV as a measure of ventricular repolarization variability in one-year-olds of GDM mothers compared to healthy controls (p < 0.05). ConclusionWe have found increased very low frequency HRV in females and decreased QTV in male children of GDM mothers, which suggests diverse responses and could reflect increased sympathetic tone and altered ventricular myocardium at a cellular level, respectively. Further work is required to understand the long-term significance of these findings in terms of providing an easy-to-use and cost-effective technology for early diagnosis of myocardial damage.

Variation in the Quanta-to-Energy Ratio of Photosynthetically Active Radiation under the Cloudless Atmosphere

The quanta-to-energy ratio plays a crucial role in converting energy units to quantum units in the context of photosynthetically active radiation (PAR). Despite its widespread use, the effects of atmospheric particles and solar zenith angle (SZA) on the quanta-to-energy ratio remain unclear. In this study, both simulation and observation data revealed that the principal wavelength, which can be transformed into the quanta-to-energy ratio using a constant, exhibits a slow initial growth, followed by a rapid increase beyond 60° solar zenith angles and a subsequent dramatic decrease after reaching its maximum value. The measured quanta-to-energy ratio demonstrates a variable range of less than 3% for SZA under 70° in a cloudless atmosphere, with significant changes only occurring at zenith angles above 80°. Simulation data indicate that ozone, wind speed, surface-level pressure, surface air temperature, and relative humidity have negligible effects on the quanta-to-energy ratio. The Ångstrom exponent exerts a minor influence on the quanta-to-energy ratio by affecting diffuse radiation. Visibility, however, is found to have a substantial impact on the quanta-to-energy ratio. As a result, two relationships are established, linking the principal wavelength to visibility and the diffuse fraction of PAR. The principal wavelength serves as an effective measure of solar spectrum variability, remaining unaffected by radiation energy. This implies that atmospheric parameters which do not alter the solar spectrum will not influence the principal wavelength. The strong correlations between the principal wavelength, visibility, and the diffuse fraction of PAR suggest a broader range of applications for the principal wavelength in various research domains, opening up new avenues for exploration and potential contributions to numerous fields.