Biostatistical demonstrating structures a significant piece of various present-day natural speculations. Hereditary qualities contemplate, since its start, utilized factual ideas to comprehend noticed trial results. Some hereditary qualities researchers even contributed with factual advances with the improvement of strategies and devices. Gregor Mendel began the hereditary qualities considers examining hereditary qualities isolation designs in groups of peas and utilized measurements to clarify the gathered information.
A linkage map (otherwise called a hereditary guide) is a table for an animal varieties or trial populace that shows the situation of its known qualities or hereditary markers comparative with one another as far as recombination recurrence, as opposed to a particular actual distance along every chromosome. Linkage maps were first evolved by Alfred Sturtevant, an understudy of Thomas Hunt Morgan.
Along with the automation of our electronic equipment life, security problems become a lot of important and necessary. There square measure queries asked in our existence like “is this the correct person to be allowed to access the system?”, “is this the licensed person to perform such action?”, and “does this person belong to the current country?” there have been 2 strategies for responsive this questions: 1st one supported “what you have” and referred to as (knowledge factors), like ID cards, and therefore the other supported “what you know” and referred to as (ownership factors), but each strategies will be borrowed or traced or purloined, therefore users have to be compelled to carry several IDs and study loads of passwords.
Factor investment and Portfolio Construction Techniques a variable distribution may be a vector in multiple unremarkably distributed variables, specified any linear combination of the variables is additionally unremarkably distributed. it's largely helpful in extending the central limit theorem to multiple variables, however conjointly has applications to Bayesian reasoning and therefore machine learning, wherever the variable distribution is employed to approximate the options of some characteristics; as an example, in sleuthing faces in footage. The traditional CVaR optimisation conducts the linear optimisation exploitation historical returns. To make sure the optimized weights are strong to a particular set of ascertained returns, we tend to propose a brand new optimisation technique that we'll decision “robust minimum CVaR optimization” or Rob Min CVaR. We tend to borrow the concepts from strong optimisation (see [MIC 98] and ancient CVaR optimisation above). In summary, we tend to work historical returns to a prespecified variable distribution.
We propose in this paper, a brief review of Muth-Pareto distribution. More precisely, we discuss the concept of record values and give a treatment of some selected properties of the distribution. The properties considered include the quartiles from quantile function, entropy, and limiting distribution of minimum order statistic.We provide some plots for the distribution of lower record values and studied the behavior by varying number of record values in the sample. It was observed that variability decreases by way of increasing number of record values in the sample. The quartiles relatedto the Muth-Pareto distributionweretabularized for some selected parameter values. It is our hope that the discoveries of this paper will be beneficialfor practitioners and also a source of reference for users so as to enhanceresearch interests related to Muth- Pareto distribution and its applications.
Covid 19 that began in the end 0f 2019 has spread rapidly across continents in a short of time. This event makes most countries do not report and record the disease properly. There is considerable number of undocumented infectious individuals that should be considered when we want to estimate the Susceptible, Infectious, and Removal (SIR) parameters and to predict the future cases. The covid 19 data obtained from City of Surabaya were analyzed using Bayesian SIR modeling by BaySIR package in RStudio. The estimated and predicted medians of SIR compartment tend to decrease over time. The estimated and predicted medians of effective reproduction number tend to decrease over time. The results depend on the assumptions of SIR model to use such as the dynamic of covid 19, local government policies, and individual behavior in the community.
Our primary objective in this paper was to determine the impact of various factorsaffecting disproportionate COVID mortality rates between counties in the United States. We primarily relied on the CDC’s demographics data and the CDC’s data on COVID andcomorbidities in US counties. We used these datasets to visualize mortality rates andco-morbidity rates. Exploratory data analysis was then performed to attempt to find trends. Afterwards, we fit our data to a linear regression model to identify the factors that contributed most to the model. The most important features of our model was the proportion of the population that was male and the median age. We found that the median age of the population was a stronger predictor of COVID mortality than presence of comorbidities like diabetes and heart disease. More analysis has yet to be done on the intersection of various comorbidities and median age.
Bivariate correlation analysis is one of the most commonly used statistical methods. Unfortunately, it is generally the case that little or no attention is given to sample size determination when planning a study in which correlation analysis will be used. For example, our review of clinical research journals indicated that none of the 111 articles published in 2014 that presented correlation results provided a justification for the sample size used in the correlation analysis. There are a number of easily accessible tools that can be used to determine the required sample size for inference based on a Pearson correlation coefficient; however, we were unable to locate any widely available tools that can be used for sample size calculations for a Spearman correlation coefficient or a Kendall coefficient of concordance. In this article, we provide formulas and charts that can be used to determine the required sample size for inference based on either of these coefficients. Additional sample size charts are provided in the Supplementary Materials.
Introduction: Coronavirus disease 2019 (COVID-19) is one of the serious infectious diseases that is caused by a specific virus called syndrome coronavirus 2 viruses (SARSCoV-2). The rapid spread of COVID19 raises serious concerns about the globally growing death rate. Currently, cases are doubled in one week around the world. Recorded data shows that COVID-19 does not infect all patients equally. This opportunistic virus can affect people of any age and gender. Information about the reason for high mortality in the age group 60 and older is limited. The gender differences among all deceased are poorly known. To understand more about COVID-19, this study aims to examine the different age groups among the death and focuses on comparing genders between males and females. Method: Statistical analysis including Pearson’s Chi-squared (χ2) and binary logistic regression was conducted based on existing data to examine factors relating to death, such as age and gender. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for death. Results: The results show that males were 2.51 more likely to die of coronavirus COVID-19 than females. Moreover, the study found a significant increase in death for patients age 60 and older compared to patients age less than 40. Thus, males of 80+ age were found to be highly associated with death. Conclusions: Older people and male are more susceptible to death from COVID-19,we should pay more attention to the elderly people and male with COVID-19. This imposes providing careful health care for this population.
Context Youth tobacco use remains a prominent United States public health issue with a high economic and health burden. Method We pooled never and ever users at youth's first wave of PATH participation (waves 1-3) to estimate age of initiation for hookah, e-cigarettes, cigarettes, traditional cigars, cigarillos, and smokeless tobacco prospectively (waves 2-4). Age of initiation of each tobacco product was estimated using weighted interval-censored survival analyses. Weighted interval censoring Cox-proportional hazards regression models were used to assess the association of ever use of the TP at the first wave of PATH participation, sex, and race/ethnicity on the age of initiation of ever use of each tobacco product. Sensitivity analyses were performed to understand the impact of the recalled age of initiation for the left-censored participants by replacing the recalled age of initiation with a uniform "6" years lower bound. Results The proportion of those who ever used each tobacco product at the first wave of PATH participation ranged from 1.8% for traditional cigars to 10.4% for cigarettes. There was a significant increase in ever use of each tobacco product after the age of 14, with e-cigarettes and cigarettes showing the highest cumulative incidence of initiation by age 21, while smokeless and cigarillos recorded the lowest cumulative incidence by age 21. The adjusted Cox models showed boys initiated at earlier ages for all of these tobacco products except for hookah, which showed no difference. Similarly, apart from ever use of hookah, non-Hispanic White youth were more likely to initiate each tobacco product at earlier ages compared to Hispanic, non-Hispanic Black, and non-Hispanic Other youth. Conclusion The increased sample size and the inclusion of ever users yielded greater precision for age of initiation of each tobacco product than analyses limited to never users at the first wave of PATH participation. These analyses can help elucidate population selection criteria for estimating the age of initiation of tobacco products.
We briefly describe methods pertaining to the development of a prognostic tool for Multiple Myeloma and direct readers to detail published clinical and methods manuscripts. This short communication provides a simpler combined version of nomograms for predicting early and late survival in the context of Multiple Myeloma.
Our Biometric team was tasked with implementing a primary objective of a newly diagnosed Multiple Myeloma registry to describe practice patterns of common first-line treatment regimens and subsequent therapeutic strategies. This manuscript describes analytical visual methods we used to understand and summarize a complex data structure. We aim to present these methods in a cohesive holistic manner which threads together materials published over time, each with focused narrower objectives, deriving from this primary objective. Methods described in detail elsewhere are briefly revisited here to provide that holistic perspective and to provide details on subsequent variants in newer applications. These have also been used in clinical publications. The coding and graphical display related details corresponding to our Sankey plot clinical publication, for which our methods are unpublished, will also be provided.
Background: Promotion of smoking cessation has been proposed as one of the primary areas of focus for tobacco control in developing countries as prevalence is high over there. This paper aimed to analyze statistically quitting method followed by the smokers who wanted to quit tobacco use in the past 12 months of the survey. Methods: The paper was based on secondary data of size 9629 collected from people aged 15 years and above by the Global Adult Tobacco Survey (GATS), 2010. Descriptive analysis and binary logistic regression had been performed using STATA-13 to analyze the data. Outcome variable was whether quitting method(s) was (were) followed by the tobacco user (1. Tobacco smoker, and 2. Smokeless tobacco user) who wanted to quit tobacco use in the past 12 months of the survey and independent variables were age, gender, residential status, education, occupation and wealth index. Results: It had been found that 47.38% of smoker respondents tried to quit tobacco smoking and among them 27.13% used any method to quit. It had been also found that among the smokeless tobacco users, 31.89% tried to quit and among them 24.83% used any method to quit. Among the quitting methods, counselling was the most used method. From the logistic regression to methods used to quitting tobacco use, it had been found that age, education and wealth index were significantly associated with the use of methods to quit tobacco smoking; whereas, gender, age and wealth index were statistically significant to the use of methods to quit smokeless tobacco. Conclusions: This study suggests that more active quitting methods should be invented targeting male, younger, lower educated and poorer tobacco users to make the cessation successful in Bangladesh.
In this paper, a new distribution called the Kumaraswamy-Rani (KR) distribution, as a Special model from the class of Kumaraswamy Generalized (KW-G) distributions, is introduced. Its statistical properties are explored. Estimation parameters based on maximum likelihood are obtained. We have illustrated the performances of the proposed distribution by some simulation studies. Finally, the significance of the KR distribution in terms of modeling real data set has been highlighted before it has been compared to some one parameter lifetime distributions.
For approval of generic drug products, the United States Food and Drug Administration (FDA) has published several regulatory guidance to assist the sponsors in preparing documents, which provide substantial evidence for demonstration of bioequivalence between a generic (test) product and its innovative (reference) product (e.g., FDA, 1992, 2003) through the conduct of bioavailability and bioequivalence studies. Bioavailability and bioequivalence studies are usually conducted under crossover designs such as a standard 2x2 crossover design or a higher-order crossover design. Under a crossover design, bioequivalence is commonly evaluated using a two one-sided tests procedure (each at a 5% level of significance) or a 90% confidence interval approach. Bioequivalence is claimed if the constructed 90% confidence interval for the geometric mean ratio falls entirely within the bioequivalence limit of (80%, 125%). Statistical methods for bioequivalence evaluation are well established and widely accepted in the pharmaceutical industry since the publication of the FDA guidance in 2003. However, several practical issues are commonly encountered during the review of regulatory submissions of generic drug products. In this article, these issues are described. In addition, some recommendations for possible clarification and/or resolutions are made.
This paper is an application of randomization test for clinical, four ways cross over, trials. The response variable was the proportion of nights with hypoglycaemic episode i.e., lowering the concentration of sugar in the blood. The hypothetical data has been used to examine how persuasively the probability of an episode depends on doses. We also observed how the power, of nonparametric randomization test, was affected when data possessed missing observations with varying sample sizes at 5% level of significance. One consequence in case of missing observations was the reduction of the power of the test, due to the reduction in the actual sample size. As a remedial mean imputation approach used, dose wise and found better power results.
Background: Malnutrition is the root causes of morbidity and mortality amongst pre-school and school going children in Bangladesh. In addition, malnutrition not only affects individuals but its effects are passed from generation to generation. Hence, the study aimed to investigate the latest nutritional status of under-five children and identify the risk factors of child malnutrition in Bangladesh using Bangladesh Demographic and Health Survey-2014 along with its distribution and composition. Data and methodology: The data used for the present study has been derived from Bangladesh Demographic and Health Survey (BDHS-2014). Sample of size 6965 has been used in this study extracted from 7886 kids’ record of BDHS-2014 with information on height and weight. Descriptive analysis has been performed to know the characteristics of the study subjects. Distribution of the z-scores is investigated, too. Then nutritional status has been clustered to gender, residence and division. And finally, binary logistic regression analysis has been used to identify influential factors that are significant to child malnutrition. Results: It has been found that 12.20% of under-five children are severely stunted and 24.91% are moderately stunted. It has been also found that 3.19% of under-five children are severely wasted, 11.74% are moderately wasted, 8.34% are severely underweighted and 24.69% are moderately underweighted. The malnutrition status (stunted) does not differ significantly to gender (p-value=0.239), but does significantly differ to residence (pvalue<0.001) and to division (p-value<0.001). When adjusted to all the factors, children of age group 18-23 months are significantly and about 7 times more likely to be stunted than children of less than 6 months age (adjusted odds ratio, AOR= 6.72, 95% confidence interval (CI)=4.94, 9.14). It has been found that Female children are less likely to be stunted than male (AOR=0.89, 95% CI=0.80, 0.99). Birth interval less than 24 months is another correlates of child malnutrition (AOR=1.37, 95% CI=1.10, 1.70). Underweighted mothers are more likely to have stunted child. Children of educated parents are less likely to be stunted. Children of Sylhet division are most likely to be stunted. Children of rural areas are 16% less likely to be stunted than urban area (AOR=0.84, 95% CI=0.74, 0.96). Children of richest families are 60% less likely to be stunted than poorest group (AOR=0.40, 95% CI=0.32, 0.50). However, job of parents is not found to have significant association with nutritional status of under-five children in Bangladesh. Conclusion: In conclusion, it can be said that increasing educational facilities for mothers and fathers can improve the child nutrition. Government and policymakers may take comprehensive and concrete challenge to overcome wealth inequities. Therefore, immediate actions are required to address all these issues to improve the nutritional status of children in Bangladesh.
Background: Adequate biostatistics knowledge among healthcare professionals is imperative for understanding medical literature and practicing evidence-based medicine. This study assessed the basic and advanced knowledge in biostatistics and clinical research among healthcare workers at the King Fahad Medical City (KFMC), Riyadh, Saudi Arabia. Methods: In this cross-sectional survey, data was collected from healthcare providers using a self-administered questionnaire, having questions related to demographics, biostatistics and clinical research. Data analysis was performed using statistical package SPSS 22. Results: Of 194 participants (63 [32.5%] consultants, 52 [26.8%] residents, and 79 [40.7%] allied healthcare providers), 45.4% had positive attitude towards learning biostatistics. Only 35.1% correctly answered biostatistics and clinical research instrument-related questions. Half participants had low score, 33% had good score, and 18-19% had excellent score of basic and advanced knowledge of biostatistics and clinical research. The highest degree and number of years of experience in biostatistics after medical school graduation were significantly (χ2 (2)=16.589, p<0.001) associated with basic and advanced biostatistics knowledge scores. Conclusion: Timely and painstaking training courses in biostatistics and clinical research are needed to improve the research standards in Saudi Arabia. Interested candidates should collaborated with statisticians to improve quality of their work and enhance their statistical skills.
