Confidence Intervals for Assessing Non-Inferiority with Assay Sensitivity in a Three-Arm Trial with Normally Distributed Endpoints

Various approaches including hypothesis test and confidence interval (CI) construction have been proposed to assess non-inferiority and assay sensitivity via a known fraction or pre-specified margin in three-arm trials with continuous or discrete endpoints. However, there is little work done on the construction of the non-inferiority margin from historical data and simultaneous generalized CIs (SGCIs) in a three-arm trial with the normally distributed endpoints. Based on the generalized fiducial method and the square-and-add method, we propose two simultaneous CIs for assessing non-inferiority and assay sensitivity in a three-arm trial. For comparison, we also consider the Wald-type Bonferroni simultaneous CI and parametric bootstrap simultaneous CI. An algorithm for evaluating the optimal sample size for attaining the pre-specified power is given. Simulation studies are conducted to investigate the performance of the proposed CIs in terms of their empirical coverage probabilities. An example taken from the mildly asthmatic study is illustrated using the proposed simultaneous CIs. Empirical results show that the proposed generalized fiducial method and the square-and-add method behave better than other two compared CIs.

A tool for translating polygenic scores onto the absolute scale using summary statistics

There is growing interest in the clinical application of polygenic scores as their predictive utility increases for a range of health-related phenotypes. However, providing polygenic score predictions on the absolute scale is an important step for their safe interpretation. We have developed a method to convert polygenic scores to the absolute scale for binary and normally distributed phenotypes. This method uses summary statistics, requiring only the area-under-the-ROC curve (AUC) or variance explained (R2) by the polygenic score, and the prevalence of binary phenotypes, or mean and standard deviation of normally distributed phenotypes. Polygenic scores are converted using normal distribution theory. We also evaluate methods for estimating polygenic score AUC/R2 from genome-wide association study (GWAS) summary statistics alone. We validate the absolute risk conversion and AUC/R2 estimation using data for eight binary and three continuous phenotypes in the UK Biobank sample. When the AUC/R2 of the polygenic score is known, the observed and estimated absolute values were highly concordant. Estimates of AUC/R2 from the lassosum pseudovalidation method were most similar to the observed AUC/R2 values, though estimated values deviated substantially from the observed for autoimmune disorders. This study enables accurate interpretation of polygenic scores using only summary statistics, providing a useful tool for educational and clinical purposes. Furthermore, we have created interactive webtools implementing the conversion to the absolute (https://opain.github.io/GenoPred/PRS_to_Abs_tool.html). Several further barriers must be addressed before clinical implementation of polygenic scores, such as ensuring target individuals are well represented by the GWAS sample.

Persistent reduction of retinal microvascular vessel density in patients with moderate and severe COVID-19 disease

ObjectiveThis study aims to analyse the possible recovery or worsening in retinal microvasculature after 8 months in a previously studied COVID-19 cohort.Methods and analysisA cross-sectional case–control study and a prospective longitudinal cohort study. Participants were the subjects of our previous study who re-enrolled for a new examination including a fundus photograph (retinography), an optical coherence tomography (OCT) scan and an OCT angiography. COVID-19 diagnosed patients were divided into three groups: group 1: mild disease, asymptomatic/paucisymptomatic subjects who received outpatient care; group 2: moderate disease and group 3: severe disease, both of which required hospital admission because of pneumonia. Statistical analyses were performed using SPSS software (V.23.0). Cross-sectional intergroup differences were analysed by means of analysis of variance for normally distributed variables and the Kruskal-Wallis test for non-normally distributed ones. In reference to the prospective part of the study (intragroup differences, baseline with 8-month comparison), a paired t-test was used for normally distributed data and Wilcoxon signed ranks sum for non-normally distributed data.ResultsThe fovea-centered superficial and deep vascular densities were significantly diminished in severe cases compared with mild cases (p=0.004; p=0.003, respectively, for superficial and deep) and to controls (p=0.014; p=0.010), also in moderate cases to mild group (p=0.004; p=0.003) and to controls (p=0.012; p=0.024). In the longitudinal study, no significant statistical differences were found between baseline and 8-month follow-up vessel density values.ConclusionWe demonstrated persistent reduction in the central vascular area over time in patients with moderate and severe COVID-19.

The Relationship of Ghrelin Level with Levels of Cluster of Differentiation 4 (CD4) in Human Immunodeficiency Virus (HIV) Patients Receiving Antiretroviral (ARV) Therapy

Background: Ghrelin is primarily involved in the secretion of growth hormone (GH), glucose and lipid metabolism. HIV infection is thought to affect ghrelin levels in HIV patients, especially in patients with lipodystrophy. However, this effect is still unclear because many studies have obtained different results about low or high levels of ghrelin in people with HIV. Suppression of HIV replication with ART rapidly increases CD4 cell count. However, data on the effect of antiretroviral therapy on ghrelin levels is still scant. Aim: To examine the relationship between ghrelin levels and CD4 levels in HIV patients receiving ARV therapy. Method: This research is an observational analysis study, with cross-sectional design, implemented start from April 2020 in Tropical Diseases & Infection Polyclinic, H. Adam Malik Hospital. Blood samples were taken and examined at the Clinical Pathology Laboratory. Primary and secondary data collection from interviews and direct observation. Data will be analyzed with Pearson correlation test if normally distributed or Spearman's test if the data is not normally distributed using SPSS software. Results: A total of 43 the sample consists of 38 patient who received the AFC, 3 patients received Duviral + Efafirens, 1 patient received Tenofovir + Hiviral + Aluvia dan 1 patient received Tenofovir + Hiviral + Neviral. Demographic characteristics based on th highest ages group are 21-30 years and 31-40 years, each of which is 17 people. The correlation of ghrelin level with levels of CD4 on the HIV patient taking ARV shows a significance value of 0.943, it can be concluded that there was no significant relationship between Ghrelin levels and CD4. Conclusion: There was no correlation between ghrelin levels with CD4 levels on HIV patient receiving ARV therapy. Keywords: Ghrelin, HIV, CD4, Antiretrovirals.

Stochastic estimation of the distribution of soil water repellency on the soil surface in a humid-temperate forest

Soil water repellency (SWR) increases surface runoff and preferential flows. Thus, quantitative evaluation of SWR distribution is necessary to understand water movements. Because the variability of SWR distribution makes it difficult to measure directly, we developed a method for estimating an SWR distribution index, defined as the areal fraction of surface soil showing SWR (SWRarea). The theoretical basis of the method is as follows: (1) SWRarea is equivalent to the probability that a position on the soil surface is drier than the critical water content (CWC); SWR is present (droplets absorbed in >10 s) when the soil surface is drier than the CWC and absent when it is wetter. (2) CWC and soil moisture content (θ) are normally distributed independent variables. (3) Thus, based on probability theory, the cumulative normal distribution of θ – CWC (f(x)) can be obtained from the distributions of CWC and θ, and f(0), the cumulative probability that θ – CWC < 0, gives the SWRarea. To investigate whether the method gives reasonable results, we repeatedly measured θ at 0–5 cm depth and determined the water repellency of the soil surface at multiple points in fixed plots with different soils and topography in a humid-temperate forest. We then calculated the CWC from the observed θ–SWR relationship at each point. We tested the normality of the CWC and θ distributions and the correlation between CWC and θ. Then, we determined f(x) from the CWC and θ distributions and estimated the SWRarea on each measurement day. Although CWC and θ were both normally distributed, in many cases they were correlated. Nevertheless, the CWC–θ dependency had little effect on the estimation error, and f(x) explained 69% of the SWRarea variability. Our findings show that a stochastic approach is useful for estimating SWRarea.

Measurement Invariant but Non-Normal Treatment Responses in Guided Internet Psychotherapies for Depressive and Generalized Anxiety Disorders

Assessment of treatment response in psychotherapies can be undermined by lack of longitudinal measurement invariance (LMI) in symptom self-report inventories, by measurement error, and/or by wrong model assumptions. To understand and compare these threats to validity of outcome assessment in psychotherapy research, we studied LMI, sum scores, and Davidian Curve Item Response Theory models in a naturalistic guided internet psychotherapy treatment register of 2,218 generalized anxiety disorder (GAD) patients and 3,922 depressive disorder (DD) patients (aged ≥16 years). Symptoms were repeatedly assessed by Generalized Anxiety Disorder Assessment-7 (GAD-7) or Beck Depression Inventory. The symptom self-reports adhered to LMI under equivalence testing, suggesting sum scores are reasonable proxies for disorder status. However, the standard LMI assumption of normally distributed latent factors did not hold and inflated treatment response estimates by 0.2 to 0.3 standard deviation units compared with sum scores. Further methodological research on non-normally distributed latent constructs holds promise in advancing LMI and mental health assessment.

VARIANCE GAMMA PROCESS WITH MONTE CARLO SIMULATION AND CLOSED FORM APPROACH FOR EUROPEAN CALL OPTION PRICE DETERMINATION

The Option is widely applied in the financial sector. The Black-Scholes-Merton model is often used in calculating option prices on a stock price movement. The model uses geometric Brownian motion which assumes that the data is normally distributed. However, in reality, stock price movements can cause sharp spikes in data, resulting in nonnormal data distribution. So we need a stock price model that is not normally distributed. One of the fastest growing stock price models today is the process exponential model. The process has the ability to model data that has excess kurtosis and a longer tail (heavy tail) compared to the normal distribution. One of the members of the process is the Variance Gamma (VG) process. The VG process has three parameters which each of them, to control volatility, kurtosis and skewness. In this research, the secondary data samples of options and stocks of two companies were used, namely zoom video communications, Inc. (ZM) and Nokia Corporation (NOK). The price of call options is determined by using closed form equations and Monte Carlo simulation. The Simulation was carried out for various values until convergent result was obtained.

Enhancing English Writing Skill through POEW Strategy

This research intended to explain the factors of students’ problems at eighth grade of SMP NU Al-Hidayah Maduran on English writing. It aimed to investigate the effect of POEW (Predict, Observe, Explain, Write) strategy used on English writing to enhance student’s English writing skill. In addition, it elaborated the significant after using POEW strategy on student’s narrative English writing. This research conducted using a quantitative design a quasi experimental research by two classes of pre-test and post-test. The researchers implemented this research to eighth grade of SMP NU Al Hidayah Maduran in academic year of 2021/2022. The participants of this study taken from eighth grade of SMP NU Al-Hidayah Maduran, which consisted of two classes and devided by experimental class and control class. It was found from the result of the test that students in experimental class got higher score than students in control class. However, based on the normality testing, this research was not normally distributed. In addition, the data declared that this research was not homogeneous. Thus, the researchers did Mann Whitney U Test. Relating to the test, the result of Asymp. Sig. (2-tailed) was smaller than the probability (0.000<0.05). It meant that Ha was accepted. However, it can be concluded that there was an effect of the use POEW strategy at eighth grade of SMP NU Al-Hidayah Maduran on English writing skill.

The Effect of Laughter Therapy on Reducing Anxiety Level in Hypertension Patients

Degenerative diseases are chronic non-communicable diseases such as heart disease, hypertension, diabetes, obesity and others. One of the degenerative diseases is hypertension. Hypertension is referred to as the "Silent Killer" because it is a deadly disease, without any symptoms as a warning to sufferers. Concerns about the emergence of new problems in hypertension will cause emotional mental disorders which are often shown by anxiety disorders. One of the lifestyle modifications that can cope with hypertension is to recommend being more relaxed. One alternative for relaxation in patients with hypertension is laughter therapy. This study aims to determine the effect of laughter therapy on reducing anxiety levels in hypertension sufferers in the Work Area. Method research using Literature review related to the effect of laughter therapy on reducing anxiety level in Hypertension patient. The results of the normality of the data showed that the data were normally distributed in the intervention group and the data were not normally distributed in the control group. From the results of this study, it is hoped that laughter therapy can be given contribution to reduce anxiety levelsin hypertensive patients, so that blood pressure in hypertensive patients can be controlled.

Return Based Risk Measures for Non-Normally Distributed Returns: An Alternative Modelling Approach

Developments in the world of finance have led the authors to assess the adequacy of using the normal distribution assumptions alone in measuring risk. Cushioning against risk has always created a plethora of complexities and challenges; hence, this paper attempts to analyse statistical properties of various risk measures in a not normal distribution and provide a financial blueprint on how to manage risk. It is assumed that using old assumptions of normality alone in a distribution is not as accurate, which has led to the use of models that do not give accurate risk measures. Our empirical design of study firstly examined an overview of the use of returns in measuring risk and an assessment of the current financial environment. As an alternative to conventional measures, our paper employs a mosaic of risk techniques in order to ascertain the fact that there is no one universal risk measure. The next step involved looking at the current risk proxy measures adopted, such as the Gaussian-based, value at risk (VaR) measure. Furthermore, the authors analysed multiple alternative approaches that do not take into account the normality assumption, such as other variations of VaR, as well as econometric models that can be used in risk measurement and forecasting. Value at risk (VaR) is a widely used measure of financial risk, which provides a way of quantifying and managing the risk of a portfolio. Arguably, VaR represents the most important tool for evaluating market risk as one of the several threats to the global financial system. Upon carrying out an extensive literature review, a data set was applied which was composed of three main asset classes: bonds, equities and hedge funds. The first part was to determine to what extent returns are not normally distributed. After testing the hypothesis, it was found that the majority of returns are not normally distributed but instead exhibit skewness and kurtosis greater or less than three. The study then applied various VaR methods to measure risk in order to determine the most efficient ones. Different timelines were used to carry out stressed value at risks, and it was seen that during periods of crisis, the volatility of asset returns was higher. The other steps that followed examined the relationship of the variables, correlation tests and time series analysis conducted and led to the forecasting of the returns. It was noted that these methods could not be used in isolation. We adopted the use of a mosaic of all the methods from the VaR measures, which included studying the behaviour and relation of assets with each other. Furthermore, we also examined the environment as a whole, then applied forecasting models to accurately value returns; this gave a much more accurate and relevant risk measure as compared to the initial assumption of normality.