scholarly journals Bayesian Analysis of Cancer Data Using a 4-Component Exponential Mixture Model

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Farzana Noor ◽  
Saadia Masood ◽  
Yumna Sabar ◽  
Syed Bilal Hussain Shah ◽  
Touqeer Ahmad ◽  
...  
Keyword(s):  
Bayesian Analysis ◽  
Mixture Model ◽  
Graphical Representation ◽  
Age Groups ◽  
Model Parameters ◽  
Jeffreys Prior ◽  
Female Population ◽  
Cancer Data ◽  
Linex Loss ◽  
Exponential Mixture

Cancer is among the major public health problems as well as a burden for Pakistan. About 148,000 new patients are diagnosed with cancer each year, and almost 100,000 patients die due to this fatal disease. Lung, breast, liver, cervical, blood/bone marrow, and oral cancers are the most common cancers in Pakistan. Perhaps smoking, physical inactivity, infections, exposure to toxins, and unhealthy diet are the main factors responsible for the spread of cancer. We preferred a novel four-component mixture model under Bayesian estimation to estimate the average number of incidences and death of both genders in different age groups. For this purpose, we considered 28 different kinds of cancers diagnosed in recent years. Data of registered patients all over Pakistan in the year 2012 were taken from GLOBOCAN. All the patients were divided into 4 age groups and also split based on genders to be applied to the proposed mixture model. Bayesian analysis is performed on the data using a four-component exponential mixture model. Estimators for mixture model parameters are derived under Bayesian procedures using three different priors and two loss functions. Simulation study and graphical representation for the estimates are also presented. It is noted from analysis of real data that the Bayes estimates under LINEX loss assuming Jeffreys’ prior is more efficient for the no. of incidences in male and female. As far as no. of deaths are concerned again, LINEX loss assuming Jeffreys’ prior gives better results for the male population, but for the female population, the best loss function is SELF assuming Jeffreys’ prior.

scholarly journals Bayesian Analysis of Inverted Kumaraswamy Mixture Model with Application to Burning Velocity of Chemicals

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Farzana Noor ◽  
Saadia Masood ◽  
Mehwish Zaman ◽  
Maryam Siddiqa ◽  
Raja Asif Wagan ◽  
...  
Keyword(s):  
Bayesian Analysis ◽  
Mixture Model ◽  
Bayesian Method ◽  
Burning Velocity ◽  
Likelihood Estimation ◽  
Empirical Bayesian ◽  
Squared Error ◽  
Linex Loss ◽  
Empirical Bayesian Method ◽  
Better Than

Burning velocity of different chemicals is estimated using a model from mixed population considering inverted Kumaraswamy (IKum) distribution for component parts. Two estimation techniques maximum likelihood estimation (MLE) and Bayesian analysis are applied for estimation purposes. BEs of a mixture model are obtained using gamma, inverse beta prior, and uniform prior distribution with two loss functions. Hyperparameters are determined through the empirical Bayesian method. An extensive simulation study is also a part of the study which is used to foresee the characteristics of the presented model. Application of the IKum mixture model is presented through a real dataset. We observed from the results that Linex loss performed better than squared error loss as it resulted in lower risks. And similarly gamma prior is preferred over other priors.

AGE FEATURES OF MOLECULAR-BIOLOGICAL SUBTYPES OF BREAST CANCER IN THE REPUBLIC OF UZBEKISTAN

2018 ◽  
Vol 64 (2) ◽  
pp. 196-199
Author(s):  
Gulya Miryusupova ◽  
G. Khakimov ◽  
N. Shayusupov
Keyword(s):  
Breast Cancer ◽  
Cancer Care ◽  
Indigenous Women ◽  
Morbidity And Mortality ◽  
Breast Cancer Data ◽  
Female Population ◽  
Cancer Data ◽  
Age Related ◽  
The Republic ◽  
Age Features

According to the results of breast cancer data in the Republic of Uzbekistan in addition to the increase in morbidity and mortality from breast cancer among women the presence of age specific features among indigenous women in the direction of “rejuvenating” of the disease with all molecular-biological (phenotypic) subtypes of breast cancer were marked. Within the framework of age-related features the prevalence of the least favorable phenotypes of breast cancer was found among indigenous women: Her2/neu hyperexpressive and three times negative subtype of breast cancer. The data obtained made it possible to build a so-called population “portrait” of breast cancer on the territory of the Republic, which in turn would contribute to further improvement of cancer care for the female population of the country.

Age and gender differences in socially aversive (“dark”) personality traits

2021 ◽  
pp. 089020702098843
Author(s):  
Johanna Hartung ◽  
Martina Bader ◽  
Morten Moshagen ◽  
Oliver Wilhelm
Keyword(s):  
Personality Traits ◽  
Structural Equation ◽  
Age Groups ◽  
Dark Triad ◽  
Equation Modeling ◽  
Model Parameters ◽  
Age And Gender ◽  
Measurement Models ◽  
And Gender ◽  
Latent Means

The strong overlap of personality traits discussed under the label of “dark personality” (e.g., psychopathy, spitefulness, moral disengagement) endorses a common framework for socially aversive traits over and beyond the dark triad. Despite the rapidly growing research on socially aversive traits, there is a lack of studies addressing age-associated differences in these traits. In the present study ( N = 12,501), we investigated the structure of the D Factor of Personality across age and gender using local structural equation modeling, thereby expressing the model parameters as a quasi-continuous, nonparametric function of age. Specifically, we evaluated loadings, reliabilities, factor (co-)variances, and means across 35 locally weighted age groups (from 20 to 54 years), separately for females and males. Results indicated that measurement models were highly stable, thereby supporting the conceptualization of the D factor independent of age and gender. Men exhibited uniformly higher latent means than females and all latent means decreased with increasing age. Overall, D and its themes were invariant across age and gender. Therefore, future studies can meaningfully pursue causes of mean differences across age and between genders.

scholarly journals Trends in prevalence of gestational diabetes mellitus in Zhejiang Province, China, 2016–2018

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Meng Wang ◽  
Ru-Ying Hu ◽  
Wei-Wei Gong ◽  
Jin Pan ◽  
Fang-Rong Fei ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Rural Areas ◽  
Urban Areas ◽  
Age Groups ◽  
Zhejiang Province ◽  
Advanced Age ◽  
Female Population ◽  
Annual Prevalence

Abstract Background Limited population-based studies have investigated the secular trend of prevalence of gestational diabetes mellitus (GDM) in mainland China. Therefore, this study aimed to estimate the prevalence of GDM and time trends in Chinese female population. Methods Based on Diabetes Surveillance System of Zhejiang Province, 97,063 diagnosed GDM cases aged 20–50 years were identified from January 1, 2016 to December 31, 2018. Annual prevalence, prevalence rate ratios (PRRs) and average annual percentage change with their 95% confidence intervals (CIs) were reported. Results The age-standardized overall prevalence of GDM was reported to be 7.30% (95% CI 7.27–7.33%); 9.13% (95% CI 9.07–9.19%) in urban areas and 6.24% (95% CI 6.21–6.27%) in rural areas. Compared with 20–24 years age group, women in advanced age groups (25–50 years) were at higher risk for GDM (PRRs ranged from 1.37 to 8.95 and the 95% CIs did not include the null). Compared with rural areas, the risk for GDM was higher in urban areas (PRR: 1.69, 95% CI 1.67–1.72). The standardized annual prevalence increased from 6.02% in 2016 to 7.94% in 2018, with an average annual increase of 5.48%, and grew more rapidly in rural than urban areas (11.28% vs. 0.00%). Conclusions This study suggested a significant increase in the prevalence of GDM among Chinese female population in Zhejiang province during 2016–2018, especially in women characterized by advanced age and rural areas.

scholarly journals Qualitative speed-accuracy tradeoff effects can be explained by a diffusion/fast-guess mixture model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Roger Ratcliff ◽  
Inhan Kang
Keyword(s):  
Mixture Model ◽  
Diffusion Model ◽  
Response Times ◽  
Model Fit ◽  
Orientation Discrimination ◽  
Model Parameters ◽  
Stimulus Contrast ◽  
Accuracy Stress ◽  
Speed Accuracy ◽  
Selective Influence

AbstractRafiei and Rahnev (2021) presented an analysis of an experiment in which they manipulated speed-accuracy stress and stimulus contrast in an orientation discrimination task. They argued that the standard diffusion model could not account for the patterns of data their experiment produced. However, their experiment encouraged and produced fast guesses in the higher speed-stress conditions. These fast guesses are responses with chance accuracy and response times (RTs) less than 300 ms. We developed a simple mixture model in which fast guesses were represented by a simple normal distribution with fixed mean and standard deviation and other responses by the standard diffusion process. The model fit the whole pattern of accuracy and RTs as a function of speed/accuracy stress and stimulus contrast, including the sometimes bimodal shapes of RT distributions. In the model, speed-accuracy stress affected some model parameters while stimulus contrast affected a different one showing selective influence. Rafiei and Rahnev’s failure to fit the diffusion model was the result of driving subjects to fast guess in their experiment.

scholarly journals Family history of early onset acute lymphoblastic leukemia is suggesting genetic associations

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xinjun Li ◽  
Kristina Sundquist ◽  
Jan Sundquist ◽  
Asta Försti ◽  
Kari Hemminki
Keyword(s):  
Acute Lymphoblastic Leukemia ◽  
Lymphoblastic Leukemia ◽  
Statistical Significance ◽  
Age Groups ◽  
Age Group ◽  
Genetic Associations ◽  
Sequencing Data ◽  
Cancer Data ◽  
Group 5 ◽  
Prostate Cancers

AbstractChildhood acute lymphoblastic leukemia (ALL) has an origin in the fetal period which may distinguish it from ALL diagnosed later in life. We wanted to test whether familial risks differ in ALL diagnosed in the very early childhood from ALL diagnosed later. The Swedish nation-wide family-cancer data were used until year 2016 to calculate standardized incidence ratios (SIRs) for familial risks in ALL in three diagnostic age-groups: 0–4, 5–34 and 35 + years. Among 1335 ALL patients diagnosed before age 5, familial risks were increased for esophageal (4.78), breast (1.42), prostate (1.40) and connective tissue (2.97) cancers and leukemia (2.51, ALL 7.81). In age-group 5–34 years, rectal (1.73) and endometrial (2.40) cancer, myeloma (2.25) and leukemia (2.00, ALL 4.60) reached statistical significance. In the oldest age-group, the only association was with Hodgkin lymphoma (3.42). Diagnostic ages of family members of ALL patients were significantly lower compared to these cancers in the population for breast, prostate and rectal cancers. The patterns of increased familial cancers suggest that BRCA2 mutations could contribute to associations of ALL with breast and prostate cancers, and mismatch gene PMS2 mutations with rectal and endometrial cancers. Future DNA sequencing data will be a test for these familial predictions.

scholarly journals Temporal trends and regional disparities in cancer screening utilization: an observational Swiss claims-based study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Caroline Bähler ◽  
Beat Brüngger ◽  
Agne Ulyte ◽  
Matthias Schwenkglenks ◽  
Viktor von Wyl ◽  
...  
Keyword(s):  
Cancer Screening ◽  
Prostate Cancer Screening ◽  
Temporal Trends ◽  
Specific Antigen ◽  
Age Groups ◽  
Fecal Occult Blood ◽  
Male Population ◽  
Female Population ◽  
Psa Testing ◽  
Mammography Use

Abstract Background We examined colorectal, breast, and prostate cancer screening utilization in eligible populations within three data cross-sections, and identified factors potentially modifying cancer screening utilization in Swiss adults. Methods The study is based on health insurance claims data of the Helsana Group. The Helsana Group is one of the largest health insurers in Switzerland, insuring approximately 15% of the entire Swiss population across all regions and age groups. We assessed proportions of the eligible populations receiving colonoscopy/fecal occult blood testing (FOBT), mammography, or prostate-specific antigen (PSA) testing in the years 2014, 2016, and 2018, and calculated average marginal effects of individual, temporal, regional, insurance-, supply-, and system-related variables on testing utilization using logistic regression. Results Overall, 8.3% of the eligible population received colonoscopy/FOBT in 2014, 8.9% in 2016, and 9.2% in 2018. In these years, 20.9, 21.2, and 20.4% of the eligible female population received mammography, and 30.5, 31.1, and 31.8% of the eligible male population had PSA testing. Adjusted testing utilization varied little between 2014 and 2018; there was an increasing trend of 0.8% (0.6–1.0%) for colonoscopy/FOBT and of 0.5% (0.2–0.8%) for PSA testing, while mammography use decreased by 1.5% (1.2–1.7%). Generally, testing utilization was higher in French-speaking and Italian-speaking compared to German-speaking region for all screening types. Cantonal programs for breast cancer screening were associated with an increase of 7.1% in mammography utilization. In contrast, a high density of relevant specialist physicians showed null or even negative associations with screening utilization. Conclusions Variation in cancer screening utilization was modest over time, but considerable between regions. Regional variation was highest for mammography use where recommendations are debated most controversially, and the implementation of programs differed the most.

Strategies to Enhance the Performance of Gaussian Mixture Model Fitting for Uncertainty Quantification by Conditioning to Production Data

2021 ◽  
Author(s):  
Guohua Gao ◽  
Jeroen Vink ◽  
Fredrik Saaf ◽  
Terence Wells
Keyword(s):  
Gaussian Mixture Model ◽  
Mixture Model ◽  
History Matching ◽  
Gaussian Mixture ◽  
Model Parameters ◽  
Gaussian Component ◽  
Large Set ◽  
Cpu Time ◽  
Fitting Method ◽  
New Strategies

Abstract When formulating history matching within the Bayesian framework, we may quantify the uncertainty of model parameters and production forecasts using conditional realizations sampled from the posterior probability density function (PDF). It is quite challenging to sample such a posterior PDF. Some methods e.g., Markov chain Monte Carlo (MCMC), are very expensive (e.g., MCMC) while others are cheaper but may generate biased samples. In this paper, we propose an unconstrained Gaussian Mixture Model (GMM) fitting method to approximate the posterior PDF and investigate new strategies to further enhance its performance. To reduce the CPU time of handling bound constraints, we reformulate the GMM fitting formulation such that an unconstrained optimization algorithm can be applied to find the optimal solution of unknown GMM parameters. To obtain a sufficiently accurate GMM approximation with the lowest number of Gaussian components, we generate random initial guesses, remove components with very small or very large mixture weights after each GMM fitting iteration and prevent their reappearance using a dedicated filter. To prevent overfitting, we only add a new Gaussian component if the quality of the GMM approximation on a (large) set of blind-test data sufficiently improves. The unconstrained GMM fitting method with the new strategies proposed in this paper is validated using nonlinear toy problems and then applied to a synthetic history matching example. It can construct a GMM approximation of the posterior PDF that is comparable to the MCMC method, and it is significantly more efficient than the constrained GMM fitting formulation, e.g., reducing the CPU time by a factor of 800 to 7300 for problems we tested, which makes it quite attractive for large scale history matching problems.

scholarly journals Smoking during pregnancy in Finland – Trends in the MATEX cohort

2018 ◽  
Vol 47 (8) ◽  
pp. 890-898 ◽  
Author(s):  
Isabell K. Rumrich ◽  
Kirsi Vähäkangas ◽  
Matti Viluksela ◽  
Mika Gissler ◽  
Heljä-Marja Surcel ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Young Women ◽  
Trigger Point ◽  
Age Groups ◽  
Smoking Behaviour ◽  
Smoking Rate ◽  
Female Population ◽  
Smoking During Pregnancy ◽  
Spatial Trends ◽  
Eastern Finland

Aims: In Finland, smoking rates in the general population are decreasing due to increased awareness of the adverse effects and tightened tobacco legislation. However, previous studies have shown that smoking in pregnant Finnish women remained as high as in the general Finnish female population at around 15% in 2010. Our aim was to describe temporal and spatial trends in smoking behaviour, and determinants of changes in smoking behaviour between first and second pregnancy. Methods: Self-reported smoking from the Finnish Medical Birth Register covered the years 1991–2015 ( N=1,435,009). The association of maternal age and socioeconomic status with smoking rate was analysed. Spatial trends were assessed at municipality level. Results: The overall smoking rate during early pregnancy remained fairly stable at around 15% from 1991 to 2015, but increased in teenage and young women below 25 years of age. The mean smoking rate (36%) was higher in these age groups than in older pregnant women (11%). Through the study period the smoking rate remained higher in blue collar workers compared with higher socioeconomic groups. Between the first and second child, on average only 4% of women started to smoke and 41% quitted. Smoking rates developed less favourably in Eastern Finland. Conclusions: The observed increase in smoking rate during pregnancy in teenage and young women is concerning. Pregnancy is a trigger point for smoking cessation in a big fraction of pregnant women. More studies are needed to explain the opposite trends of smoking rates in Northern and Western Finland compared with Eastern Finland.

scholarly journals The physical activity and health status of two generations of Black South African professional women

2011 ◽  
Vol 16 (1) ◽  
Author(s):  
Cheryl M. Walter ◽  
Rosa Du Randt ◽  
Daniel J.L. Venter
Keyword(s):  
Physical Activity ◽  
Health Status ◽  
Black Women ◽  
South African ◽  
Age Groups ◽  
Overweight And Obesity ◽  
Professional Women ◽  
Female Population ◽  
Two Generations ◽  
Health Promoting

Increased health risks associated with physical inactivity in the Black population have been reported in recent years. Black women, suffering the highest levels of inactivity, overweight and obesity, are at greatest risk of developing chronic diseases of lifestyle. This explorativedescriptive study investigated the physical activity patterns and health status of two generations of Black professional women, reflecting pre-democracy and post-democracy age groups. Quantitative measures were used, including the ActiGraph GT1M accelerometer, the Global Physical Activity Questionnaire and the Health-Promoting Lifestyle Profile. Sample groups comprised teachers, nurses, social workers and public sector managers. Participants aged between 35 and 45 years were allocated to the older generation group (n = 111), whilst those aged between 18 and 21 years (students in the mentioned professional fields) were allocated to the younger generation group (n = 69). The results indicated that these women displayed lower levels of health-promoting behavioural practices than expected, significantly lower levels of physical activity and significantly higher levels of overweight and obesity than the South African norms. The observation that the younger group appeared to be replicating the patterns of the older women is a cause of concern. Greater compliance to health-promoting behaviours was expected in this group owing to participants’ professional involvement in health, education and social development fields. Wide-ranging initiatives are necessary to promote physical activity and health amongst the Black female population in South Africa.Opsomming Gedurende die afgelope jare het navorsing onder die Swart bevolking ʼn toename in gesondheidsrisiko’s wat met fisieke onaktiwiteit geassosieer is, getoon. Swart vroue, wat die hoogste vlakke van onaktiwiteit, oorgewig en obesiteit toon, blyk ook die grootste risiko te loop om leefstylverwante chroniese siektes te ontwikkel. Hierdie ondersoekendbeskrywende studie het die fisieke aktiwiteitspatrone en gesondheidstatus van twee generasies van Swart professionele vroue ondersoek. Die tweegenerasiesteekproef verteenwoordig voor- en na-demokrasie-ouderdomsgroepe. Kwantitatiewe meetinstrumente, naamlik die ActiGraph GT1M versnellingsmeter, Globale Fisieke Aktiwiteitsvraelys en die Gesondheidsbevorderende Leefstylprofiel is gebruik. Die steekproef het onderwysers, verpleegkundiges, maatskaplike werkers en bestuurders in die openbare sektor ingesluit. Deelnemers tussen 35 en 45 jaar is aan die ouergenerasie-toetsgroep toegewys (n = 111), terwyl dié tussen 18 en 21 jaar (studente in bogenoemde studierigtings) aan die jongergenerasietoetsgroep toegewys is (n = 69). Die resultate het gewys dat die Swart professionele vroue laer as verwagte gesondheidsbevorderende gedrag, betekenisvol laer vlakke van fisieke aktiwiteit en betekenisvol hoër vlakke van oorgewig en obesiteit toon as die Suid-Afrikaanse norme. Die waarneming dat die jonger groep dieselfde gedragspatrone as die ouer vroue getoon het, is ʼn bron van kommer. ʼn Groter nakoming van gesondheidsbevorderende gedrag is onder die jonger groep vroue verwag, aangesien hulle hul opleiding in die professionele sektor van gesondheid, onderwys en maatskaplike werk ontvang. ʼn Holistiese benadering is nodig om fisieke aktiwiteit en gesondheid onder Swart Suid-Afrikaanse vrouens te bevorder.

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