Statistical Inferences of Burr XII Lifetime Models under Joint Type-1 Competing Risks Samples

The problem of statistical inference under joint censoring samples has received considerable attention in the past few years. In this paper, we adopted this problem when units under the test fail with different causes of failure which is known by the competing risks model. The model is formulated under consideration that only two independent causes of failure and the unit are collected from two lines of production and its life distributed with Burr XII lifetime distribution. So, under Type-I joint competing risks samples, we obtained the maximum likelihood (ML) and Bayes estimators. Interval estimation is discussed through asymptotic confidence interval, bootstrap confidence intervals, and Bayes credible interval. The numerical computations which described the quality of theoretical results are discussed in the forms of real data analyzed and Monte Carlo simulation study. Finally, numerical results are discussed and listed through some points as a brief comment.

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Parametric and Semiparametric Estimations of Bivariate Truncated Type I Generalized Logistic Models driven from Copulas

International Journal of Statistics and Probability ◽

10.5539/ijsp.v7n1p72 ◽

2017 ◽

Vol 7 (1) ◽

pp. 72 ◽

Cited By ~ 2

Author(s):

Lamya A Baharith

Keyword(s):

Logistic Models ◽

Real Data ◽

Information Criterion ◽

Logistic Distribution ◽

Type I ◽

Copula Functions ◽

Data Set ◽

Monte Carlo Simulation Study ◽

Generalized Logistic Distribution ◽

Weibull Models

Truncated type I generalized logistic distribution has been used in a variety of applications. In this article, a new bivariate truncated type I generalized logistic (BTTGL) distributional models driven from three different copula functions are introduced. A study of some properties is illustrated. Parametric and semiparametric methods are used to estimate the parameters of the BTTGL models. Maximum likelihood and inference function for margin estimates of the BTTGL parameters are compared with semiparametric estimates using real data set. Further, a comparison between BTTGL, bivariate generalized exponential and bivariate exponentiated Weibull models is conducted using Akaike information criterion and the maximized log-likelihood. Extensive Monte Carlo simulation study is carried out for different values of the parameters and different sample sizes to compare the performance of parametric and semiparametric estimators based on relative mean square error.

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Health related quality of life among children with Type I diabetes, Assiut city, Egypt

Journal of Nursing Education and Practice ◽

10.5430/jnep.v7n10p73 ◽

2017 ◽

Vol 7 (10) ◽

pp. 73 ◽

Cited By ~ 2

Author(s):

Marzoka A. Gadallah ◽

Taghreed Abdul-Aziz M. Ismail ◽

Naglaa Saad Abdel Aty

Keyword(s):

Quality Of Life ◽

Type 1 Diabetes ◽

Health Insurance ◽

Type I Diabetes ◽

Type I ◽

Health Related Quality ◽

Related Quality ◽

Health Related

Objective: Health related quality of life (HRQOL) is a multidimensional construct that includes physical and psychosocial functioning, has emerged as an important outcome in pediatric population with chronic health conditions. The study objectives are to measure the quality of life among children with type I diabetes compared to healthy peers and to determine factors affecting the QOL among children with type I diabetes.Methods: Analytic cross sectional study was conducted in Sidi Galal health insurance outpatient clinic for children with type 1 diabetes mellitus and a comparison group of healthy peers was taken from other outpatient clinics. A total of four hundred and twelve children, aged from 8-18 years with type 1 diabetes and four hundred and twelve healthy peers matched in age and sex were interviewed. Three tools were used for this study: Demographic questionnaire, Socio-economic scale, and Peds QL4.0 Generic Core Scale was used to measure HRQOL.Results: The mean age of studied children was 12.9 ± 3.2. More than 60% of children with diabetes had uncontrolled glycemic level and 60% of them were in low socio-economic level. Children with diabetes had significantly lower HRQOL than healthy children in all domains. Age, glycemic control status and birth order of the diabetic children showed no significance difference regarding the QOL. Disease duration affected only the emotional function of the QOL and females showed significantly higher score regarding school functioning. Social, school and the total QOL scores were significantly higher among children with highly educated mothers while father's education affected the emotional, school and total QOL scores. Children in the middle and high social class showed significantly higher scores regarding social, school and total QOL. Presence of diabetic parent positively affected the social functioning while had negative effect on the school function of children with type I diabetes.Conclusions and recommendations: Diabetes is negatively affecting all the QOL functioning of the children. We recommend that Integrated programs between child's home, school and health insurance clinics for educating and supporting children with diabetes to improve their HRQOL.

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Quality of Life in Romanian Children with Type 1 Diabetes: A Cross-Sectional Survey Using an Interdisciplinary Healthcare Intervention

Healthcare ◽

10.3390/healthcare8040382 ◽

2020 ◽

Vol 8 (4) ◽

pp. 382

Author(s):

Constanta Urzeală ◽

Aura Bota ◽

Silvia Teodorescu ◽

Mihaela Vlăiculescu ◽

Julien S Baker ◽

...

Keyword(s):

Quality Of Life ◽

Type 1 Diabetes ◽

Well Being ◽

Healthcare Intervention ◽

Type I ◽

Cross Sectional ◽

Significant Difference ◽

Interdisciplinary Healthcare

Background: The purpose of this study was to assess the quality of life in Romanian type 1 diabetes mellitus (T1DM) children attending an early interdisciplinary healthcare intervention. Hypothesis: engaging T1DM children in leisure sports leads to a better quality of life. Methods: This research embeds a cross-sectional observational study, incorporating some clinical characteristics relevant for diabetes management. The Kidscreen 27 questionnaire was issued to 100 T1DM children aged between 7 and 17 years. Parents completed the questionnaire. All subjects received interdisciplinary healthcare in the previous year. Statistics were performed using SPSS, v20. The required sample size of 100 subjects was obtained with a confidence interval of 95% and a sampling error of 0.009. The tests were two-sided, with a type I error set at 0.05. Results: Subjects reached an increased level of physical well-being, psychological well-being, autonomy, parent relationships, peer and social support, and school inclusion. There was a significant difference (p < 0.05) between children who practice leisure activities and children who only participated in physical education (PE) classes, regarding their physical well-being (t = 2.123). ANOVA demonstrated significant differences between age groups regarding physical well-being. Conclusion: The interdisciplinary healthcare intervention increased the efficiency of T1DM management with positive effects on life quality.

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A comparative analysis of cell-type adjustment methods for epigenome-wide association studies based on simulated and real data sets

Briefings in Bioinformatics ◽

10.1093/bib/bby068 ◽

2018 ◽

Vol 20 (6) ◽

pp. 2055-2065 ◽

Cited By ~ 1

Author(s):

Johannes Brägelmann ◽

Justo Lorenzo Bermejo

Keyword(s):

Statistical Power ◽

Type I Error ◽

Association Studies ◽

Real Data ◽

Error Rates ◽

Data Sets ◽

Type I ◽

Cell Type ◽

Type I Error Rates

Abstract Technological advances and reduced costs of high-density methylation arrays have led to an increasing number of association studies on the possible relationship between human disease and epigenetic variability. DNA samples from peripheral blood or other tissue types are analyzed in epigenome-wide association studies (EWAS) to detect methylation differences related to a particular phenotype. Since information on the cell-type composition of the sample is generally not available and methylation profiles are cell-type specific, statistical methods have been developed for adjustment of cell-type heterogeneity in EWAS. In this study we systematically compared five popular adjustment methods: the factored spectrally transformed linear mixed model (FaST-LMM-EWASher), the sparse principal component analysis algorithm ReFACTor, surrogate variable analysis (SVA), independent SVA (ISVA) and an optimized version of SVA (SmartSVA). We used real data and applied a multilayered simulation framework to assess the type I error rate, the statistical power and the quality of estimated methylation differences according to major study characteristics. While all five adjustment methods improved false-positive rates compared with unadjusted analyses, FaST-LMM-EWASher resulted in the lowest type I error rate at the expense of low statistical power. SVA efficiently corrected for cell-type heterogeneity in EWAS up to 200 cases and 200 controls, but did not control type I error rates in larger studies. Results based on real data sets confirmed simulation findings with the strongest control of type I error rates by FaST-LMM-EWASher and SmartSVA. Overall, ReFACTor, ISVA and SmartSVA showed the best comparable statistical power, quality of estimated methylation differences and runtime.

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On Reliability in a Multicomponent Stress-Strength Model with Power Lindley Distribution

Revista Colombiana de Estadística ◽

10.15446/rce.v41n2.69621 ◽

2018 ◽

Vol 41 (2) ◽

pp. 251-267 ◽

Cited By ~ 6

Author(s):

Abbas Pak ◽

Arjun Kumar Gupta ◽

Nayereh Bagheri Khoolenjani

Keyword(s):

Interval Estimation ◽

Parametric Bootstrap ◽

Real Data ◽

Credible Interval ◽

Data Sets ◽

Strength Model ◽

Reliability Parameter ◽

Posterior Density ◽

Bayes Estimate ◽

Highest Posterior Density

In this paper we study the reliability of a multicomponent stress-strength model assuming that the components follow power Lindley model. The maximum likelihood estimate of the reliability parameter and its asymptotic confidence interval are obtained. Applying the parametric Bootstrap technique, interval estimation of the reliability is presented. Also, the Bayes estimate and highest posterior density credible interval of the reliability parameter are derived using suitable priors on the parameters. Because there is no closed form for the Bayes estimate, we use the Markov Chain Monte Carlo method to obtain approximate Bayes estimate of the reliability. To evaluate the performances of different procedures, simulation studies are conducted and an example of real data sets is provided.

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Quality of Life for Parents of Children and Adolescents With Type 1 Diabetes

The Diabetes Educator ◽

10.1177/014572179802400607 ◽

1998 ◽

Vol 24 (6) ◽

pp. 721-727 ◽

Cited By ~ 22

Author(s):

Melissa Spezia Faulkner ◽

Frances Sholar Clark

Keyword(s):

Quality Of Life ◽

Life Satisfaction ◽

Children And Adolescents ◽

Type I Diabetes ◽

Type I ◽

Life Questionnaire ◽

School Aged Children ◽

The Family

The purpose of this study was to examine the issue of quality of life (QOL) of parents with children and adolescents with type I diabetes. Parental QOL was measured by the Parents Diabetes Quality of Life Questionnaire. Parental life satisfaction was most affected by the burden the child's diabetes placed on the family. The event having the most impact on parental QOL was the frequency of telling others about the child's diabetes. The greatest worry was that the child would develop complications from diabetes. Parents of school-aged children experienced significantly greater life satisfaction than parents of adolescents. Married parents had higher life satisfaction than those who were divorced. Metabolic control, reflected by HbA1c values, was associated with the life satisfaction of parents.

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Health-Related Quality of Life, Family Conflicts and Fear of Injecting: Perception Differences between Preadolescents and Adolescents with Type 1 Diabetes and Their Mothers

Behavioral Sciences ◽

10.3390/bs11070098 ◽

2021 ◽

Vol 11 (7) ◽

pp. 98

Author(s):

Marta Tremolada ◽

Maria Cusinato ◽

Sabrina Bonichini ◽

Arianna Fabris ◽

Claudia Gabrielli ◽

...

Keyword(s):

Quality Of Life ◽

Diabetes Mellitus ◽

Type 1 Diabetes ◽

Self Regulation ◽

Type I ◽

Family Conflicts ◽

Cross Sectional ◽

Age Range

Good management of diabetes requires at the same time self-regulation behaviour and a balanced involvement of family components. This cross-sectional study’s aims were: understanding fear of injections and perceptions of family conflicts in preadolescents and adolescents with type 1 diabetes mellitus and their mothers, comparing their perceptions, and identifying the risk factors impacting patients’ quality of life. Eligibility criteria were: treatment for diabetes mellitus type I, currently aged 10–18 years, attending the hospital for annual hospital follow-ups. Exclusion criteria were: intellectual disabilities, inability to complete questionnaires alone and neuropsychiatric illness with active pharmacotherapy. The study design was cross-sectional. Participants were one hundred and two patients (Mean age = 14.6, SD = 2.4; age range = 10–19 years; Females = 52 and Males = 50) and their mothers (Mean age = 46.9, SD = 6.2, age range = 27–63 years), who filled in self and proxy-report questionnaires (N total= 204). The results showed that 20% of patients and 14.7% of their mothers reported clinical scores for fear of self-injection and blood testing. The mothers reported lower fear of injecting and higher family conflicts compared with the patients. Age, fear of injecting and family conflicts were significantly associated with patients’ quality of life perceptions. Clinical considerations and recommendations are given based on the empirical results.

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Host-Related Laboratory Parameters for Leprosy Reactions

Frontiers in Medicine ◽

10.3389/fmed.2021.694376 ◽

2021 ◽

Vol 8 ◽

Author(s):

Yuqian Luo ◽

Mitsuo Kiriya ◽

Kazunari Tanigawa ◽

Akira Kawashima ◽

Yasuhiro Nakamura ◽

...

Keyword(s):

Erythema Nodosum ◽

Clinical Symptoms ◽

Type I ◽

Leprosy Reactions ◽

Erythema Nodosum Leprosum ◽

Precise Diagnosis ◽

Reversal Reaction

Leprosy reactions are acute inflammatory episodes that complicate the course of a Mycobacterium leprae infection and are the major cause of leprosy-associated pathology. Two types of leprosy reactions with relatively distinct pathogenesis and clinical features can occur: type 1 reaction, also known as reversal reaction, and type 2 reaction, also known as erythema nodosum leprosum. These acute nerve-destructive immune exacerbations often cause irreversible disabilities and deformities, especially when diagnosis is delayed. However, there is no diagnostic test to detect or predict leprosy reactions before the onset of clinical symptoms. Identification of biomarkers for leprosy reactions, which impede the development of symptoms or correlate with early-onset, will allow precise diagnosis and timely interventions to greatly improve the patients' quality of life. Here, we review the progress of research aimed at identifying biomarkers for leprosy reactions, including its correlation with not only immunity but also genetics, transcripts, and metabolites, providing an understanding of the immune dysfunction and inflammation that underly the pathogenesis of leprosy reactions. Nevertheless, no biomarkers that can reliably predict the subsequent occurrence of leprosy reactions from non-reactional patients and distinguish type I reaction from type II have yet been found.

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Kinematic Analysis of the Musculoskeletal System Diabetic Type I

European Scientific Journal ESJ ◽

10.19044/esj.2018.v14n15p414 ◽

2018 ◽

Vol 14 (15) ◽

pp. 414

Author(s):

Khaled Atiyat ◽

Osama "Abdul Fattah" ◽

Ayed Ali Zureigat

Keyword(s):

Musculoskeletal System ◽

Kinematic Analysis ◽

Natural Extension ◽

Video Camera ◽

Type I ◽

Diabetic Type ◽

Type1 Diabetes ◽

Study Results

This study aimed to apply the principles of biomechanics science correctly, also to be is nested in the treatment of diabetics, and establish kinematic record for musculoskeletal diabetics. In order to improve the quality of life and care for diabetics. To achieve this, the researchers used the kinematic analysis of the musculoskeletal system for (8) mail patients with type1 diabetes, purposive selected and belonging to Jordanian team of Diabetes (age: 21±0.7years, height: 164± 4 cm, mas:58± 0.2 kg, the experience of the disease, 13.3±0.8 years). The study sample was filmed by using video camera (Sony HDR-CX220E) reached speed (50) frame/s. The study results showed that musculoskeletal system for Diabetic Type I differences in their shape of musculoskeletal the rest of the population, consequently people with Type 1 Diabetes have a swayback posture and a lower chest forward posture. and the average of sample study in the flexion spine(77)° and (15)°for extension spine. Where it formed 81% from natural flexion spine and 45% from natural extension spine. The researchers recommend: the necessity informed Diabetic Type I on kinematic analysis of the musculoskeletal system.

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Statistical Analysis of Joint Type-I Generalized Hybrid Censoring Data from Burr XII Lifetime Distributions

Complexity ◽

10.1155/2021/5543187 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Mahmoud Ragab ◽

Aisha Fayomi ◽

Ali Algarni ◽

G. A. Abd-Elmougod ◽

Neveen Sayed-Ahmed ◽

...

Keyword(s):

Model Parameters ◽

Type I ◽

Bayes Method ◽

Monte Carlo Simulation Study ◽

Lifetime Distributions ◽

Hybrid Censoring ◽

Life Tests ◽

Censoring Scheme ◽

Theoretical Results

The quality of the products coming from different lines of production requires some tests called comparative life tests. For lines having the same facility, the lifetime of the product is distributed by Burr XII, the lifetime distribution, and units are tested under type-I generalized hybrid censoring scheme. The observed censoring data are used under maximum likelihood and the Bayes method to estimate the model parameters. The theoretical results are discussed and assessed through data analysis and Monte Carlo simulation study. Finally, we reported some brief comments obtained from numerical computation.

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