Browsing by Author "Rakesh Ranjan"

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A Bayes Analysis and Comparison of Arrhenius Weibull and Arrhenius Lognormal Models under Competing Risk
(Taylor and Francis Ltd., 2023) Ankita Gupta; Rakesh Ranjan; Satyanshu K. Upadhyay
The paper considers constant stress accelerated life test situations under a competing risk scenario. The different groups of experimental units are operated at different accelerated levels of stress and, at each level, the units are exposed to fail from two competing causes of failures. For modeling the failure times resulting from such a test, the paper considers two competing risk models. The first model is based on the minimum of two Weibull failure times whereas the second one is based on the minimum of two lognormal failure times. In order to study the effect of covariates on failure times, the scale parameter of component models in each modeling framework has been regressed using the Arrhenius relationship. The paper performs a complete Bayes analysis of both the considered models for a real dataset arising from a temperature accelerated life test experiment and compares the two models using a few standard Bayesian tools. Bayes analysis is done using vague but proper priors for the parameters. Moreover, the considered models result in to intractable posterior distributions and, therefore, the paper uses the Metropolis algorithm to draw the desired posterior based inferences. For censored data situations, however, the intermediate Gibbs steps are used as updating mechanism by defining full conditionals corresponding to unknown censored data. The plausibility of both the models for entertained dataset has also been checked before performing their comparison. A numerical example based on a real dataset is provided for illustration. © 2022 Taylor & Francis Group, LLC.
A Bayes analysis of a competing risk model based on gamma and exponential failures
(Elsevier Ltd, 2015) Rakesh Ranjan; Sonam Singh; Satyanshu K. Upadhyay
The paper proposes a competing risk model based on minimum of gamma and exponential failures where the former reflects aging with shape greater than unity and latter corresponds to accidental failures. The proposed model is analyzed in a Bayesian framework using proper but weak priors for the parameters. The analysis is done using Markov chain Monte Carlo simulation, in particular, the Gibbs sampler with intermediate Metropolis steps. Some usual characterizations of the proposed model are given for completeness. The proposed procedures are finally illustrated by means of a simulated data example involving both accidental and aging failures. The paper also considers model compatibility study using the ideas of predictive simulation and compares the proposed model with its components based on the simulated data set. A comparison with a similar model based on increasing hazard rate Weibull and exponential failures is also given. The results are found to be satisfactory. © 2015 Published by Elsevier Ltd.
A Bayes Analysis of a Dependent Competing Risk Model Based on Marshall-Olkin Bivariate Weibull Distribution
(World Scientific, 2023) Ankita Gupta; Rakesh Ranjan; Akanksha Gupta; Satyanshu K. Upadhyay
This paper considers a competing risk model defined on the basis of minimum of two dependent failures where the two failures are assumed to jointly follow Marshall-Olkin bivariate Weibull distribution. This paper explores some important features of corresponding likelihood functions and performs a full Bayesian analysis of the model for data resulting from normal as well as accelerated life tests. The accelerated model is described by regressing the scale parameters of the model through inverse power-law relationship. Posterior-based inferences are drawn using the Gibbs sampler algorithm after specifying proper but vague priors for the model parameters. The numerical illustration is provided using real datasets. The performance of the model is assured by Bayesian tools of model compatibility and then the entertained model is compared with the competing risk model based on Marshall-Olkin bivariate exponential assumption. © 2023 World Scientific Publishing Company.
A prospective randomized comparison of simultaneous integrated boost with sequential boost intensity-modulated radiotherapy in locally advanced head and neck cancer
(Wolters Kluwer Medknow Publications, 2022) Nilesh Mani; Sushil K. Aggarwal; Ishan Kumar; Abhijit Mandal; Garima Jaiswal; Rakesh Ranjan; Anil K. Jaiswal; Neha Gupta; Ankita Singh; Ankur Mourya; Lalit M. Aggarwal; Sunil Choudhary
Purpose: A comparison of simultaneous integrated boost (SIB) with sequential boost (SEQ) using intensity-modulated radiotherapy along with concurrent cisplatin in locally advanced head and neck cancer (HNC) was made with regard to their survival outcomes and toxicity profile. Materials and Methods: A total of 34 patients were enrolled between October 2016 and March 2019. They were randomized into two arms, SIB and SEQB. All patients were treated with 6 MV photon beam on Linear Accelerator with weekly concurrent cisplatin at 35 mg/m 2. Overall survival (OS) and disease-free survival (DFS) were the primary end points and acute and late toxicities were the secondary end points. Results: The median follow-up period was 40.6 and 37.3 months for SIB and SEQB, respectively. At the end of 5 years, the median OS was 40.6 and 37.3 months (P = 0.947) and the median DFS was 35.1 and 37.3 months in the SIB and SEQB arms, respectively (P = 0.991).complete response at 3 months was 64.7% and 76.5% and partial response was 23.5% and 17.6%, whereas progressive disease was 11.8% and 5.9% in SIB and SEQB arms, respectively. Acute dermatitis, mucositis, dysphagia, and salivary gland toxicities were higher in the SIB arm compared to the SEQB arm. Conclusion: SIB and SEQ arms were comparable in terms of OS and DFS. However, the acute toxicities were higher in the SIB arm, although the difference was not significant, compared to the SEQB arm. © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
A simple Bayes analysis of Weibull Based Accelerated Test model
(Springer, 2017) Rijji Sen; Rakesh Ranjan; S.K. Upadhyay
This paper considers a simple Bayes analysis of a two-parameter Weibull distribution in an accelerated test scenario when the scale parameter is regressed according to power law relationship. The analysis is done using independent, vague priors for the parameters. Experiments involving both complete and censored data sets are assumed from the model. Appropriate numerical illustrations are provided using real datasets. The results are found to be satisfactory. © 2015, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.
Bayes analysis of some important lifetime models using MCMC based approaches when the observations are left truncated and right censored
(Elsevier Ltd, 2021) Rakesh Ranjan; Rijji Sen; Satyanshu K. Upadhyay
The paper considers the Bayes analysis of important lifetime models such as the Weibull, the gamma, and the lognormal distributions when the available data are left truncated and right-censored. Weakly informative prior distributions are employed for the purpose. Two well-known Markov chain Monte Carlo based approaches, namely, the Metropolis algorithm and the Hamiltonian Monte Carlo technique are used to draw samples from analytically intractable posterior distributions. Besides, the paper does a comparative study of the three entertained models using Bayes factor. The paper has considered calculating the marginal likelihood using bridge sampler algorithm for evaluating the necessary Bayes factor. Finally, a numerical illustration based on a real dataset compares the two algorithms and draws relevant conclusions appropriately. © 2021 Elsevier Ltd
Bayes analysis of the generalized gamma AFT models for left truncated and right censored data
(Taylor and Francis Ltd., 2023) Asmita Shukla; Rakesh Ranjan; Satyanshu K. Upadhyay
This article considers the Bayes analysis of generalized gamma accelerated failure time model and its two components Weibull and gamma when the given observations are left truncated and right censored. In order to perform the analysis, the paper proposes the use of an improved version of the Metropolis-Hastings algorithm, namely, the Metropolis-adjusted Langevin algorithm. Besides, the paper also checks the model compatibility and compares the considered models with its components using the Bayes factor computed on the basis of a recent methodology. A numerical illustration is provided based on a simulated as well as a real dataset. The real dataset consists of individuals infected with human immunodeficiency virus who are at the risk of acquired immunodeficiency syndrome and subsequent deaths. The numerical illustration is further extended to check the effect of different therapies including the highly active antiretroviral therapy on the lifetime of individuals. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
Bayes Analysis of Weibull Regression Model with Variable Selection: A Study Using Shrinkage Prior
(Taylor and Francis Ltd., 2025) Asmita Shukla; Rakesh Ranjan; Satyanshu Kumar Upadhyay
This article considers the Bayes analysis of the Weibull regression model when a number of covariates are involved in the model. Considering appropriate prior distributions for the model parameters and independent Laplace priors for the regression coefficients, the Bayes analysis is performed using the Gibbs sampler algorithm. Both empirical Bayes and hierarchical Bayes approaches are used to deal with the shrinkage parameter involved in the Laplace prior. Since the final objective is variable selection, the article uses Bayesian least absolute selection and shrinkage operator for the same. A comparison of the full model with the reduced model is done using a few important Bayesian tools. Finally, the numerical illustration is provided using both simulated and a real data set of comprehensive Micro-Ribonucleic acid profiling of nasopharyngeal carcinoma specimens. It may be noted that such an analysis might be useful in a variety of fields, including medical research, reliability analysis and several other experiments involving time to event data. © 2025 Taylor & Francis Group, LLC.
Bayes point predictors of exponential distribution under asymmetric loss when observations are multiply type II censored
(Natural Sciences Publishing, 2018) Vastoshpati Shastri; Rakesh Ranjan; Deependra S. Pal
The crux of this paper is to obtain predictors of the future observation under multiply type II censored sample from exponential distribution. Bayes point predictors are obtained under asymmetric loss function (linear) as well as under symmetric loss function (squared error) using nature conjugate prior. Predictive risks are calculated under each loss. Predictors are compared for the smallest ordered future observation on the basis of predictive risk efficiencies for 1000 randomly generated sample using Monte Carlo simulation technique as well as for real informative data representing failure times for electric insulation. © 2018 NSP.
Bayesian analysis of competing risk models with high dimensional covariates with an application to adenocarcinoma survival data
(Taylor and Francis Ltd., 2025) Rakesh Ranjan; A. Bhattacharjee; Rijji Sen; Satyanshu Kumar Upadhyay
This paper analyses competing risk models with high dimensional covariates when the number of observations is comparatively quite small. This gives rise to a very typical situation where most statistical estimates become unstable and non-unique. Thus dimension reduction by carrying out variable selection becomes a very imperative part of the study. This is performed using both classical and Bayesian tools. Lifetimes under each risk is assumed to follow either the Weibull or the exponential distribution and a total of four models is formed using a combination of these risks. Bayesian analysis of the resulting four models are performed via Markov chain Monte Carlo methods. A real life application is provided for adenocarcinoma micro-array data. Finally, model selection is carried out using deviance information criterion. © 2025 Taylor & Francis Group, LLC.
Bayesian Parameter Estimation and Model Selection for Gallbladder Cancer Data of two Countries
(Natural Sciences Publishing, 2022) Richa Srivastava; Rakesh Ranjan; Himanshu Misra
The paper proposes statistical model and complete Bayesian inference for cancer survival data of two countries. Complete posterior analysis is done by generating random samples from posterior surface. Gibbs sampler, a Markov chain Monte Carlo (MCMC) method has been used, for generating samples from posterior distribution. The paper also provides algorithm for Gibbs sampler generation scheme for proposed model parameters as well its density estimation. Model compatibility and inter model comparisons, using the measures of Bayesian information criterion (BIC) and deviance information criterion (DIC) has been used. © 2022 NSP
Bayesian prediction limits for inverse weibull distribution when observations are mid type II censored
(Natural Sciences Publishing, 2021) Vastoshpati Shastri; Rakesh Ranjan; Deependra Singh Pal
In this paper, the problem of prediction is discussed for inverse Weibull distribution. Posterior distribution is obtained using different informative priors when observations are mid type II censored. When the shape parameter of the model is known, prediction interval is obtained using predictive probability density function method. Whereas, when both parameters are known, inferences from the posterior distribution are drawn using Bayes computation. Comparisons have been made on the basis of simulated data set for the smallest ordered future observation. © 2021 NSP Natural Sciences Publishing Cor.
Chemical constituents of artabotrys odoratissimus (SEEDS)
(2009) Jagdish P. Singh; Alok K. Singh; Archana Singh; Rakesh Ranjan
3-Hydroxy-9-methoxypterocarpan, nonacosanoic acid 2', 3'-dihydroxypropyl ester, pentacosanoic acid 2,-3'-dihydroxypropyl ester and docosanoic acid have been isolated for the first time from the seeds of Artabotrys odoratissimus and identified by spectroscopic data of these natural products and their derivatives.
Chemical investigation of Annona squamosa (stem bark)
(2010) Rakesh Ranjan; Subra Singh; Seema Tiwari; K.K. Singh
4, 9-Dihydroxy -3, 8-dimethoxy- benzo [4, 5] furo [3, 2-C] chromen -6- one, 6, 7′-dihydroxy -3-methoxydihydroflavonol, 5,7- dihydroxy -4′-methoxy isoflavone, 7-hydroxy -4′-methoxy isoflavone, 7,3′-dihydroxy -4′-methoxy isoflavone, 4′, 5, 7-trihydroxy isoflavone, 2′- hydoxy genistein have been isolated for the first time from the stem bark of Annona squamosa and identified by spectroscopic data.
Classical and bayes analysis of a competing risk model based on two weibull distributions with increasing and decreasing hazards
(Gnedenko Forum, 2018) Ankita Gupta; Rakesh Ranjan; Satyanshu K. Upadhyay
The paper considers a competing risk model based on two Weibull distributions, one with increasing and the other with decreasing hazard rate. It then considers both classical and Bayesian analysis of the model, the later development utilizes the informative but weak priors for the parameters. The analysis is facilitated by the fact that a competing risk model can be considered as an incomplete data model even if the situation allows all the observations on the test to be made available although the results are extended for censored data cases as well. The paper uses the expectation-maximization algorithm for classical maximum likelihood estimation and Gibbs sampler algorithm for posterior based inferences. It is shown that the likelihood function offers unique and consistent maximum likelihood estimates. The results are illustrated based on a real data example. Finally, the compatibility of the model is examined for the considered real data set using some standard tools of Bayesian paradigm. © 2018 Reliability: Theory and Applications. All rights reserved.
Classical and Bayesian Estimation for the Parameters of a Competing Risk Model Based on Minimum of Exponential and Gamma Failures
(Institute of Electrical and Electronics Engineers Inc., 2016) Rakesh Ranjan; S.K. Upadhyay
The paper provides both classical and Bayesian estimation of the parameters of a competing risk model defined on the basis of minimum of exponential and gamma failure modes. Usually such situations are the examples of incomplete specification of data that naturally opens the way to expectation maximization algorithm for obtaining maximum likelihood estimates of model parameters. This incomplete specification of the data simultaneously explores the possibility of sampling importance resampling strategy with intermediate Markov chain Monte Carlo steps for the Bayesian estimation of parameters. Although this paper focuses primarily on estimation of model parameters, other inferential developments can be routinely done. Numerical illustration is provided based on both simulated and real-data examples. © 2016 IEEE.
Comparison of two hypofractionated radiotherapy schedules in locally advanced postmastectomy breast cancer patients
(Wolters Kluwer Medknow Publications, 2020) Sunil Choudhary; Neha Gupta; Shagun Misra; Narvada Narain Munnee; Amit Kumar; Rakesh Ranjan; Sovan Sarang Dhar; Deepak Kumar; Ankur Mourya; Lalit Mohan Aggarwal
Introduction: The role of hypofractionated radiotherapy (HFRT) in postmastectomy breast cancer patients is not well established. This study was done to establish the role of two different HFRT schedules in the treatment of chest wall and regional lymph nodes after mastectomy. Materials and Methods: Between 2012 and 2016, consecutively registered patients of locally advanced breast cancer patients having undergone mastectomy and adjuvant radiotherapy (RT) at a tertiary cancer center were analyzed. Locoregional recurrence (LRR) was the primary endpoint, whereas overall survival (OS), disease-free survival (DFS), and both acute and late adverse events were secondary endpoints. Results: A total of 34 patients who were treated with 39 Gy in 13 fractions over 2½ weeks and 35 patients who were treated with 40 Gy in 15 fractions over 3 weeks were identified. The median follow-up period was 47 months and 63.5 months in the 39 Gy and 40 Gy arms, respectively. LRR was seen in 11.8% and 8.6% of patients in the 39 Gy and 40 Gy arms, respectively. OS at 4 years was 66% and 71.5% in the 39 Gy and 40 Gy arms, respectively. The mean DFS for 39 Gy and 40 Gy arms was 43.6 months and 66.4 months, respectively (P = 0.822). Acute skin toxicity was similar in the two groups. Arm edema was significantly more in the 40 Gy arm. Conclusion: The two HFRT schedules are equivalent to each other in terms of survival outcomes. Arm edema is higher with 40 Gy arm as compared to 39 Gy arm. © 2020 Journal of Cancer Research and Therapeutics | Published by Wolters Kluwer - Medknow.
Coumarinolignans from the seeds of Annona squamosa Linn.
(WWW Publications PTE India, 2009) Rakesh Ranjan; Mahendra Sahai
Phytochemical investigations of Annona squamosa seeds have led to the isolation of three lignans consisting of coumarin moiety, cleomiscosin A(1), cleomiscosin B(2) and cleomiscosin C(3). Their structures were arrived at by detailed spectroscopic analysis. Cleomiscosin A and cleomiscosin B are position isomer.
Effect of persistent organic pollutants in patients with ischemic stroke and all stroke: A systematic review and meta-analysis
(Elsevier Ireland Ltd, 2023) Priya Dev; Kamalesh Chakravarty; Manoj Pandey; Rakesh Ranjan; Mareena Cyriac; Vijaya Nath Mishra; Abhishek Pathak
The role of environmental contaminants and their association with stroke is still being determined. Association has been shown with air pollution, noise, and water pollution; however, the results are inconsistent across studies. A systematic review and meta-analysis of the effect of persistent organic pollutants (POP) in ischemic stroke patients were conducted; a comprehensive literature search was carried out until 30th June 2021 from different databases. The quality of all the articles which met our inclusion criteria was assessed using Newcastle-Ottawa scaling; five eligible studies were included in our systematic review. The most studied POP in ischemic stroke was polychlorinated biphenyls (PCBs), and they have shown a trend for association with ischemic stroke. The study also revealed that living near a source of POPs contamination constitutes a risk of exposure and an increased risk of ischemic stroke. Although our study provides a strong positive association of POPs with ischemic stroke, more extensive studies must be conducted to prove the association. © 2023
Flavone glycodsides of Annona reticulata (seeds)
(2008) Rakesh Ranjan; Subhra Singh; Seema Tiwari; K.K. Singh
3′-O-β-D-glucopyranosyl [2″, 3: 7,8] furanotlavone, 3-methoxy-6-O-β-D-glucopyranosyl [2″, 3: 7,8] furanoflavone, 3-methoxy- 3′, 4′-methylenedioxy-7-O-β-D-glucopyranosylflavone and apigeniin-7-β-glucoronicacid 6″-butyl ester have been isolated first time from the seeds of Annona reticulata and identified by spectroscopic data.