scholarly journals Guidance for practitioners on the choices of software implementation for frailty models: Simulations and an application in determining the birth interval dynamics

2018 ◽  
Vol 52 (1) ◽  
pp. 1-17
Author(s):  
MOHAMMAD EHSANUL KARIM ◽  
JAHIDUR RAHMAN KHAN
Keyword(s):  
Birth Interval ◽  
Frailty Model ◽  
Frailty Models ◽  
Parameter Estimates ◽  
R Software ◽  
Number Of Clusters ◽  
Software Packages ◽  
Software Implementations ◽  
Heterogeneity Parameter ◽  
The Stability

In clustered survival analysis applications, researchers frequently fit frailty models using parametric and nonparametric approaches to obtain the estimates for the parameters associated with the survival model covariates and heterogeneity (frailty). Availability of the off- the-shelve implementations and freely available R software packages makes it convenient for the practitioners to fit these complicated models easily. Even though there has been a couple of studies assessing the stability of the older packages (e.g., survival, coxme) under a variety of scenarios, some of the newer implementations (e.g., frailtySurv, JM and parfm) have not gone through similar rigorous assessment. It is worth evaluating these new software implementations, and comparing them with the older packages. In the current work, via simulations, we will examine the estimates from all of these popularly used software implementations under a variety of scenarios when the corresponding assumptions related to the baseline hazard and frailty distributions are misspecified. Additionally, true heterogeneity parameter, censoring patterns and number of clusters were varied in the simulations to assess respective impacts on the estimates. From these simulations, we observed that when there is a large number of clusters and mild censoring, Cox PH frailty models fitted using a newer semiparametric estimation technique (from the frailtySurv package) produced regression and heterogeneity parameter estimates that were associated with unusually large bias and variability. On the other hand, when the true heterogeneity parameter is substantially large, the Cox PH frailty models fitted using the coxme package were often producing highly variable estimates of the heterogeneity parameter. The simulation findings then guided our choice of appropriate frailty model in the context of determining the birth interval dynamics in Bangladesh.

The use of software packages of R factoextra and FactoMineR and their application in principal component analysis for authentication of oils

2020 ◽  
pp. 1
Author(s):  
Irnawati Irnawati ◽  
Florentinus Dika Octa Riswanto ◽  
Sugeng Riyanto ◽  
Sudibyo Martono ◽  
Abdul Rohman
Keyword(s):  
Principal Component Analysis ◽  
Human Life ◽  
Virgin Olive Oil ◽  
Principal Component ◽  
Extra Virgin Olive Oil ◽  
Component Analysis ◽  
R Software ◽  
Software Packages ◽  
Similar Chemical ◽  
Potential Benefits

Several oils have been reported as nutritional source and providing potential benefits for human life. Oil adulteration becomes major issue due to economical attempt to reduce the price of high cost oils. The employment of FTIR spectroscopy combined with Principal Component Analysis (PCA) technique can be applied in oils authentication study. Two of R software packages namely factoextra and FactoMineR were exploited to perform PCA for analysis sixteen various oils from market in Yogyakarta, Indonesia. The results showed that PCA model have been successfully generated using these two statistical packages. Individual plot, variable plot, and biplot were presented to visualize the PCA model. It was also proved that extra virgin olive oil (EVOO) has similar chemical characteristics to palm oil (PO) as reported in the previous study.

scholarly journals A Bayesian phylogenetic approach to estimating the stability of linguistic features and the genetic biasing of tone

2010 ◽  
Vol 278 (1704) ◽  
pp. 474-479 ◽  
Author(s):  
Dan Dediu
Keyword(s):  
Cultural Transmission ◽  
Linguistic Diversity ◽  
Large Set ◽  
Linguistic Features ◽  
Major Interest ◽  
Software Implementations ◽  
Phylogenetic Framework ◽  
Linguistic Tone ◽  
The Stability ◽  
Stable Characteristic

Language is a hallmark of our species and understanding linguistic diversity is an area of major interest. Genetic factors influencing the cultural transmission of language provide a powerful and elegant explanation for aspects of the present day linguistic diversity and a window into the emergence and evolution of language. In particular, it has recently been proposed that linguistic tone —the usage of voice pitch to convey lexical and grammatical meaning—is biased by two genes involved in brain growth and development, ASPM and Microcephalin . This hypothesis predicts that tone is a stable characteristic of language because of its ‘genetic anchoring’. The present paper tests this prediction using a Bayesian phylogenetic framework applied to a large set of linguistic features and language families, using multiple software implementations, data codings, stability estimations, linguistic classifications and outgroup choices. The results of these different methods and datasets show a large agreement, suggesting that this approach produces reliable estimates of the stability of linguistic data. Moreover, linguistic tone is found to be stable across methods and datasets, providing suggestive support for the hypothesis of genetic influences on its distribution.

Gamma frailty model for survival risk estimation: an application to cancer data

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
K. M. J. Krishna ◽  
T. Traison ◽  
Sejil Mariya Sebastian ◽  
Preethi Sara George ◽  
Aleyamma Mathew
Keyword(s):  
Proportional Hazards ◽  
Risk Estimation ◽  
Univariate Analysis ◽  
Frailty Model ◽  
Cox Proportional Hazards ◽  
Information Criteria ◽  
Frailty Models ◽  
Event Analysis ◽  
Global Test ◽  
Cancer Data

Abstract Objectives: In time to event analysis, the risk for an event is usually estimated using Cox proportional hazards (CPH) model. But CPH model has the limitation of biased estimate due to unobserved hidden heterogeneity among the covariates, which can be tackled using frailty models. The best models were usually being identified using Akaike information criteria (AIC). Apart from AIC, the present study aimed to assess predictability of risk models using survival concordance measure. Methods: CPH model and frailty models were used to estimate the risk for breast cancer patient survival, and the frailty variable was assumed to follow gamma distribution. Schoenfeld global test was used to check the proportionality assumption. Survival concordance, AIC and simulation studies were used to identify the significance of frailty. Results: From the univariate analysis it was observed that for the covariate age, the frailty has a significant role (θ = 2.758, p-value: 0.0004) and the corresponding hazard rate was 1.93 compared to that of 1.38 for CPH model (age > 50 vs. ≤ 40). Also the covariates radiotherapy and chemotherapy were found to be significant (θ = 5.944, p-value: <0.001 and θ = 16, p-value: <0.001 respectively). Even though there were only minor differences in hazard rates, the concordance was higher for frailty than CPH model for all the covariates. Further the simulation study showed that the bias and root mean square error (RMSE) obtained for both the methods was almost the same and the concordance measures were higher for frailty model by 12–15%. Conclusions: We conclude that the frailty model is better compared to CPH model as it can account for unobserved random heterogeneity, and if the frailty coefficient doesn’t have an effect it gives exactly the same risk as that of CPH model and this has been established using survival concordance.

​Genetic Variability Studies in Short Statured Early Maturing M3 Generation Cluster Bean [Cyamopsis tetragonoloba (L.) Taub.] Mutants

2021 ◽  
Author(s):  
P. Balasubramanian ◽  
C. Vanniarajan ◽  
V. Swaminathan ◽  
J. Souframanien ◽  
Devi Suresh ◽  
...  
Keyword(s):  
Combination Treatment ◽  
Gamma Ray ◽  
Phenotypic Variance ◽  
Cyamopsis Tetragonoloba ◽  
Number Of Clusters ◽  
Cluster Bean ◽  
Pod Yield ◽  
Early Maturing ◽  
The Stability ◽  
Pod Length

Background: The present germplasm of cluster bean lack the needed natural variability for developing early maturing short statured lines. Therefore, an attempt was made to study the magnitude of heritable variability stimulated through induced mutation in M3 generation. Methods: M3 generation seeds of cluster bean variety MDU1 treated with gamma rays, electron beam and combination of gamma ray with EMS were used in the present investigation. The biometric observations were recorded on ten selected M3 plants from each family of every treatments for six traits viz., plant height, days to first flowering, number of clusters per plant, number of pods per plant, pod length and pod yield per plant. The same method was followed for recording observations on untreated parental materials also. Result: Studies on the variability parameters indicated that the phenotypic variance, genotypic variance, heritability and genetic advance were higher in combination treatment for all the traits. The shortest mutant and the earliest flowering (3M11) was observed in combination of 100 Gy of gamma ray+20 mM EMS. Mutant for the highest number of clusters (3M3) was observed in combination treatment of 300 Gy gamma ray with 20 mM EMS. The mutants for the highest number of pods per plant (3M1 and 3M2) and the highest pod yield (3M1) were identified at 400 Gy of gamma ray treatment. Fifteen desirable mutants were selected and forwarded to next generation for testing the stability in different environments.

scholarly journals A Mixture Shared Inverse Gaussian Frailty Model under Modified Weibull Baseline Distribution

2020 ◽  
Vol 49 (2) ◽  
pp. 31-42
Author(s):  
Ralte Lalpawimawha ◽  
Arvind Pandey
Keyword(s):  
Infectious Disease ◽  
Monte Carlo ◽  
Frailty Model ◽  
Frailty Models ◽  
Matched Pairs ◽  
Inverse Gaussian ◽  
Bivariate Data ◽  
Modified Weibull ◽  
True Values ◽  
The Bayesian Approach

Frailty models are used in the survival analysis to account for the unobserved heterogeneityin individual risks to disease and death. To analyze the bivariate data on relatedsurvival times (e.g. matched pairs experiments, twin or family data), the shared frailtymodels were suggested. In this manuscript, we propose a new mixture shared inverse Gaussian frailty model based on modified Weibull as baseline distribution. The Bayesian approach of Markov Chain Monte Carlo technique is employed to estimate the parameters involved in the models. In addition, a simulation study is performed to compare the true values of the parameters with the estimated values. A comparison with the existing model was done by using Bayesian comparison techniques. A better model for infectious disease data related to kidney infection is suggested.

Determinants of Time-to-recovery from Hypertension using a Comparison of Various Parametric Shared Frailty Models: In Case of Felege Hiwot Refral Hospital.

2021 ◽  
Author(s):  
Nigist Mulu ◽  
Yeshambel Kindu ◽  
Abay Kassie
Keyword(s):  
Survival Time ◽  
Blood Urea Nitrogen ◽  
Normal Condition ◽  
Recovery Time ◽  
Frailty Model ◽  
Frailty Models ◽  
Inverse Gaussian ◽  
Urea Nitrogen ◽  
Shared Frailty Model ◽  
Shared Frailty

Abstract Background: Hypertension is a major public health problem that is responsible for morbidity and mortality. In Ethiopia hypertension is becoming a double burden due to urbanization. The study aimed to identify factors that affect time-to-recovery from hypertension at Felege Hiwot Referral Hospital. Retrospective study design was used at FHRH. Methods: The data was collected in patient’s chart from September 2016 to January 2018. Kaplan-Meier survival estimate and Log-Rank test were used to compare the survival time. The AFT and parametric shared frailty models were employed to identify factors associated with the recovery time of hypertension patients. All the fitted models were compared by using AIC and BIC. Results: Eighty one percent of sampled patients were recovered to normal condition and nineteen percent of patients were censored observations. The median survival time of hypertensive patients to attain normal condition was 13 months. Weibull- inverse Gaussian shared frailty model was found to be the best model for predicting recovery time of hypertension patients. The unobserved heterogeneity in residences as estimated by the Weibull-Inverse Gaussian shared frailty model was θ=0.385 (p-value=0.00). Conclusion: The final model showed that age, systolic blood pressure, related disease, creantine, blood urea nitrogen and the interaction between blood urea nitrogen and age were the determinants factors of recovery status of patients at 5% level of significance. The result showed that patients creantine >1.5 Mg/dl compared to creantine ≤1.5 Mg/dl and SBP were prolonged the recovery time of patients whereas patients having kidney disease, other disease and had no any disease compared to diabetic patients and the interaction BUN and age were shorten recovery status of hypertension patients.

scholarly journals Evolution of communities of software: using tensor decompositions to compare software ecosystems

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Oliver A. Blanthorn ◽  
Colin M. Caine ◽  
Eva M. Navarro-López
Keyword(s):  
Dynamic Network ◽  
Tensor Decomposition ◽  
Software Projects ◽  
R Software ◽  
Tensor Decompositions ◽  
Software Ecosystems ◽  
Software Libraries ◽  
Dependency Networks ◽  
Software Packages ◽  
Over Time

AbstractModern software development is often a collaborative effort involving many authors through the re-use and sharing of code through software libraries. Modern software “ecosystems” are complex socio-technical systems which can be represented as a multilayer dynamic network. Many of these libraries and software packages are open-source and developed in the open on sites such as , so there is a large amount of data available about these networks. Studying these networks could be of interest to anyone choosing or designing a programming language. In this work, we use tensor factorisation to explore the dynamics of communities of software, and then compare these dynamics between languages on a dataset of approximately 1 million software projects. We hope to be able to inform the debate on software dependencies that has been recently re-ignited by the malicious takeover of the npm package and other incidents through giving a clearer picture of the structure of software dependency networks, and by exploring how the choices of language designers—for example, in the size of standard libraries, or the standards to which packages are held before admission to a language ecosystem is granted—may have shaped their language ecosystems. We establish that adjusted mutual information is a valid metric by which to assess the number of communities in a tensor decomposition and find that there are striking differences between the communities found across different software ecosystems and that communities do experience large and interpretable changes in activity over time. The differences between the elm and R software ecosystems, which see some communities decline over time, and the more conventional software ecosystems of Python, Java and JavaScript, which do not see many declining communities, are particularly marked.

Pattern and determinant factors of birth intervals among Iranian women: a semi-parametric multilevel survival model

2019 ◽  
Vol 52 (4) ◽  
pp. 534-546
Author(s):  
Maryam Seyedtabib ◽  
Abbas Moghimbeigi ◽  
Mahmood Mahmoudi ◽  
Reza Majdzadeh ◽  
Hossein Mahjub
Keyword(s):  
Mass Media ◽  
Birth Interval ◽  
Family Income ◽  
Contraceptive Use ◽  
Frailty Model ◽  
Population Heterogeneity ◽  
Iranian Women ◽  
Birth Intervals ◽  
Effective Role ◽  
Using Data

AbstractThe interval between successive pregnancies (birth interval) is one of the main indexes used to evaluate the health of a mother and her child. This study evaluated birth intervals in Iran using data from the Iranian Multiple Indicators Demographic and Health Survey (IrMIDHS) conducted in 2010–2011. A total of 20,093 married Iranian women aged 15–54 years from the whole country constituted the study sample. Based on the nature of sampling and the unobserved population heterogeneity for birth intervals in each city and province, a multilevel survival frailty model was applied. Data were analysed for women’s first three birth intervals. The median first and second birth intervals were 30.3 and 39.7 months respectively. Higher education, Caesarean delivery, contraceptive use and exposure to public mass media were found to decrease the hazard rate ratio (HRR) of giving birth. Meanwhile, higher monthly income increased the hazard of giving birth. The results suggest that public mass media can play an effective role in encouraging women to have the recommended birth interval. Furthermore, increasing family income could encourage Iranian couples to decrease the time to their next birth.

scholarly journals Validating fPSA Glycoprofile as a Prostate Cancer Biomarker to Avoid Unnecessary Biopsies and Re-Biopsies

Cancers ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2988
Author(s):  
Tomas Bertok ◽  
Eduard Jane ◽  
Aniko Bertokova ◽  
Lenka Lorencova ◽  
Peter Zvara ◽  
...  
Keyword(s):  
Clinical Performance ◽  
Receiver Operating Curve ◽  
Low Grade ◽  
Clinical Validation ◽  
Serum Samples ◽  
R Software ◽  
Software Packages ◽  
Auc Value ◽  
Clinically Significant ◽  
Receiver Operating

Background: To compare the clinical performance of a new PCa serum biomarker based on fPSA glycoprofiling to fPSA% and PHI. Methods: Serum samples from men who underwent prostate biopsy due to increased PSA were used. A comparison between two equal groups (with histologically confirmed PCa or benign, non-cancer condition) was used for the clinical validation of a new glycan-based PCa oncomarker. SPSS and R software packages were used for the multiparametric analyses of the receiver operating curve (ROC) and for genetic algorithm metaheuristics. Results: When comparing the non-cancer and PCa cohorts, the combination of four fPSA glycoforms with two clinical parameters (PGI, prostate glycan index (PGI)) showed an area under receiver operating curve (AUC) value of 0.821 (95% CI 0.754–0.890). AUC values were 0.517 for PSA, 0.683 for fPSA%, and 0.737 for PHI. A glycan analysis was also applied to discriminate low-grade tumors (GS = 6) from significant tumors (GS ≥ 7). Conclusions: Compared to PSA on its own, or fPSA% and the PHI, PGI showed improved discrimination between presence and absence of PCa and in predicting clinically significant PCa. In addition, the use of PGI would help practitioners avoid 63.5% of unnecessary biopsies, while the use of fPSA% and PHI would help avoid 17.5% and 33.3% of biopsies, respectively, while missing four significant tumors (9.5%).

scholarly journals NONLINEAR ERROR CORRECTION: THE CASE OF MONEY DEMAND IN THE UNITED KINGDOM (1878–2000)

2004 ◽  
Vol 8 (1) ◽  
pp. 76-116 ◽  
Author(s):  
ALVARO ESCRIBANO
Keyword(s):  
Error Correction ◽  
Money Demand ◽  
Smoothing Splines ◽  
Single Equation ◽  
Parametric Models ◽  
Parameter Estimates ◽  
Nonlinear Error ◽  
Rational Polynomial ◽  
Long Run ◽  
The Stability

This paper explores single-equation nonlinear error correction (NEC) models with linear and nonlinear cointegrated variables. Within the class of semiparametric NEC models, we use smoothing splines. Within the class of parametric models, we discuss the interesting properties of cubic polynomial NEC models and we show how they can be used to identify unknown threshold points in asymmetric models and to check the stability properties of the long-run equilibrium. A new class of rational polynomial NEC models is also introduced. We found multiple long-run money demand equilibria. The stability observed in the money-demand parameter estimates during more than a century, 1878 to 2000, is remarkable.

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