Ram Tiwari - Academia.edu (original) (raw)

Papers by Ram Tiwari

Research paper thumbnail of Assessing noninferiority in a three-arm trial using the Bayesian approach

Statistics in Medicine, Apr 26, 2011

Research paper thumbnail of Breast Cancer Survival, Competing Risks and Mixture Cure Model: A Bayesian Analysis

Journal of the Royal Statistical Society, Nov 9, 2009

Research paper thumbnail of Bootstrapping a Bayes estimator of a survival function with censored data

Annals of the Institute of Statistical Mathematics

Research paper thumbnail of A Propensity-Score Integrated Approach to Bayesian Dynamic Power Prior Borrowing

arXiv (Cornell University), Oct 4, 2022

Research paper thumbnail of Interpreting p-Values and Confidence Intervals Using Well-Calibrated Null Preference Priors

Research paper thumbnail of Augmenting Both Arms of a Randomized Controlled Trial Using External Data: An Application of the Propensity Score-Integrated Approaches

Statistics in Biosciences, 2021

Research paper thumbnail of Mitigating Study Power Loss Caused by Clinical Trial Disruptions Due to the COVID-19 Pandemic: Leveraging External Data via Propensity Score-Integrated Approaches

Statistics in Biopharmaceutical Research, 2021

Research paper thumbnail of Semiparametric Bayesian Markov analysis of personalized benefit–risk assessment

Annals of Applied Statistics, 2020

Research paper thumbnail of Meta analysis of binary data with excessive zeros in two-arm trials

Journal of Statistical Distributions and Applications, 2019

Research paper thumbnail of Non-inferiority testing for risk ratio, odds ratio and number needed to treat in three-arm trial

Computational Statistics & Data Analysis, 2019

Research paper thumbnail of Bayesian hierarchical methods for meta-analysis combining randomized-controlled and single-arm studies

Statistical methods in medical research, 2018

Meta-analysis of interventions usually relies on randomized controlled trials. However, when the ... more Meta-analysis of interventions usually relies on randomized controlled trials. However, when the dominant source of information comes from single-arm studies, or when the results from randomized controlled trials lack generalization due to strict inclusion and exclusion criteria, it is vital to synthesize both sources of evidence. One challenge of synthesizing both sources is that single-arm studies are usually less reliable than randomized controlled trials due to selection bias and confounding factors. In this paper, we propose a Bayesian hierarchical framework for the purpose of bias reduction and efficiency gain. Under this framework, three methods are proposed: bivariate generalized linear mixed effects models, hierarchical power prior model and hierarchical commensurate prior model. Design difference and potential biases are considered in all models, within which the hierarchical power prior and hierarchical commensurate prior models further offer to downweight single-arm stud...

Research paper thumbnail of Bayesian approach for assessing non-inferiority in a three-arm trial with pre-specified margin

Statistics in medicine, Jan 4, 2015

Non-inferiority trials are becoming increasingly popular for comparative effectiveness research. ... more Non-inferiority trials are becoming increasingly popular for comparative effectiveness research. However, inclusion of the placebo arm, whenever possible, gives rise to a three-arm trial which has lesser burdensome assumptions than a standard two-arm non-inferiority trial. Most of the past developments in a three-arm trial consider defining a pre-specified fraction of unknown effect size of reference drug, that is, without directly specifying a fixed non-inferiority margin. However, in some recent developments, a more direct approach is being considered with pre-specified fixed margin albeit in the frequentist setup. Bayesian paradigm provides a natural path to integrate historical and current trials' information via sequential learning. In this paper, we propose a Bayesian approach for simultaneous testing of non-inferiority and assay sensitivity in a three-arm trial with normal responses. For the experimental arm, in absence of historical information, non-informative priors ar...

Research paper thumbnail of Bayesian nonparametric inference

Institute of Mathematical Statistics Lecture Notes - Monograph Series, 1992

Research paper thumbnail of CONVERGENCE OF DIRICHLET MEASURES AND THE INTERPRETATION OF THEIR PARAMETER11Research supported by the U.S. Army Research Office under Grant no. DAAG 29-79-C-0158. The United States Government is authorized to reproduce and distribute reprints for governmental purposes

Statistical Decision Theory and Related Topics III, 1982

The form of the Bayes estimate of the population mean with respect to a Dirichlet prior with para... more The form of the Bayes estimate of the population mean with respect to a Dirichlet prior with parameter a has given rise to the interpretation that a ( X ) is the prior sample size. Furthermore, if a ( X ) is made to tend to zero, then the Bayes estimate mathematically converges to the classical estimator, that is, the sample mean. This has further given rise to the general feeling that allowing a ( X ) to become small not only makes the prior sample size small but also that it corresponds to no prior information. By investigating the limits of prior distributions as the parameter a tends to various values, it is misleading to think of a ( X ) as the prior sample size and the smallness of a ( X ) as no prior information. In fact, very small values of a ( X ) actually mean that the prior has a lot of information concerning the unknown true distribution and is of a form that would be generally unacceptable to a statistician.

Research paper thumbnail of Assessing noninferiority in a three‐arm trial using the Bayesian approach

Statistics in Medicine, 2011

Non‐inferiority trials, which aim to demonstrate that a test product is not worse than a competit... more Non‐inferiority trials, which aim to demonstrate that a test product is not worse than a competitor by more than a pre‐specified small amount, are of great importance to the pharmaceutical community. As a result, methodology for designing and analyzing such trials is required, and developing new methods for such analysis is an important area of statistical research. The three‐arm trial consists of a placebo, a reference and an experimental treatment, and simultaneously tests the superiority of the reference over the placebo along with comparing this reference to an experimental treatment. In this paper, we consider the analysis of noninferiority trials using Bayesian methods which incorporate both parametric as well as semi‐parametric models. The resulting testing approach is both flexible and robust. The benefit of the proposed Bayesian methods is assessed via simulation, based on a study examining home‐based blood pressure interventions. Copyright © 2011 John Wiley & Sons, Ltd.

Research paper thumbnail of Modeling Population-Based Cancer Survival Trends Using Joinpoint Survival Models

In the United States cancer as a whole is the second leading cause of death and a major burden to... more In the United States cancer as a whole is the second leading cause of death and a major burden to health care, thus the medical progress against cancer is a major public health goal. There are many individ- ual studies to suggest that cancer treatment breakthroughs and early diagnosis have significantly improved the prognosis of cancer patients. To better understand

Research paper thumbnail of Nonparametric and Semiparametric Bayesian Reliability Analysis

Encyclopedia of Statistics in Quality and Reliability, 2008

Research paper thumbnail of Modelling Population-Based Cancer Survival Trends by using Join Point Models for Grouped Survival Data

Journal of the Royal Statistical Society Series A: Statistics in Society, 2009

SummaryIn the USA cancer as a whole is the second leading cause of death and a major burden to he... more SummaryIn the USA cancer as a whole is the second leading cause of death and a major burden to health care; thus medical progress against cancer is a major public health goal. There are many individual studies to suggest that cancer treatment breakthroughs and early diagnosis have significantly improved the prognosis of cancer patients. To understand better the relationship between medical improvements and the survival experience for the patient population at large, it is useful to evaluate cancer survival trends on the population level, e.g. to find out when and how much the cancer survival rates changed. We analyse population-based grouped cancer survival data by incorporating join points into the survival models. A join point survival model facilitates the identification of trends with significant change-points in cancer survival, when related to cancer treatments or interventions. The Bayesian information criterion is used to select the number of join points. The performance of ...

Research paper thumbnail of Nonparametric Bayes Estimation of Contamination Levels Using Observations from the Residual Distribution

Journal of the American Statistical Association, 2000

Research paper thumbnail of A Class of Semiparametric Mixture Cure Survival Models With Dependent Censoring

Journal of the American Statistical Association, 2009

Research paper thumbnail of Assessing noninferiority in a three-arm trial using the Bayesian approach

Statistics in Medicine, Apr 26, 2011

Research paper thumbnail of Breast Cancer Survival, Competing Risks and Mixture Cure Model: A Bayesian Analysis

Journal of the Royal Statistical Society, Nov 9, 2009

Research paper thumbnail of Bootstrapping a Bayes estimator of a survival function with censored data

Annals of the Institute of Statistical Mathematics

Research paper thumbnail of A Propensity-Score Integrated Approach to Bayesian Dynamic Power Prior Borrowing

arXiv (Cornell University), Oct 4, 2022

Research paper thumbnail of Interpreting p-Values and Confidence Intervals Using Well-Calibrated Null Preference Priors

Research paper thumbnail of Augmenting Both Arms of a Randomized Controlled Trial Using External Data: An Application of the Propensity Score-Integrated Approaches

Statistics in Biosciences, 2021

Research paper thumbnail of Mitigating Study Power Loss Caused by Clinical Trial Disruptions Due to the COVID-19 Pandemic: Leveraging External Data via Propensity Score-Integrated Approaches

Statistics in Biopharmaceutical Research, 2021

Research paper thumbnail of Semiparametric Bayesian Markov analysis of personalized benefit–risk assessment

Annals of Applied Statistics, 2020

Research paper thumbnail of Meta analysis of binary data with excessive zeros in two-arm trials

Journal of Statistical Distributions and Applications, 2019

Research paper thumbnail of Non-inferiority testing for risk ratio, odds ratio and number needed to treat in three-arm trial

Computational Statistics & Data Analysis, 2019

Research paper thumbnail of Bayesian hierarchical methods for meta-analysis combining randomized-controlled and single-arm studies

Statistical methods in medical research, 2018

Meta-analysis of interventions usually relies on randomized controlled trials. However, when the ... more Meta-analysis of interventions usually relies on randomized controlled trials. However, when the dominant source of information comes from single-arm studies, or when the results from randomized controlled trials lack generalization due to strict inclusion and exclusion criteria, it is vital to synthesize both sources of evidence. One challenge of synthesizing both sources is that single-arm studies are usually less reliable than randomized controlled trials due to selection bias and confounding factors. In this paper, we propose a Bayesian hierarchical framework for the purpose of bias reduction and efficiency gain. Under this framework, three methods are proposed: bivariate generalized linear mixed effects models, hierarchical power prior model and hierarchical commensurate prior model. Design difference and potential biases are considered in all models, within which the hierarchical power prior and hierarchical commensurate prior models further offer to downweight single-arm stud...

Research paper thumbnail of Bayesian approach for assessing non-inferiority in a three-arm trial with pre-specified margin

Statistics in medicine, Jan 4, 2015

Non-inferiority trials are becoming increasingly popular for comparative effectiveness research. ... more Non-inferiority trials are becoming increasingly popular for comparative effectiveness research. However, inclusion of the placebo arm, whenever possible, gives rise to a three-arm trial which has lesser burdensome assumptions than a standard two-arm non-inferiority trial. Most of the past developments in a three-arm trial consider defining a pre-specified fraction of unknown effect size of reference drug, that is, without directly specifying a fixed non-inferiority margin. However, in some recent developments, a more direct approach is being considered with pre-specified fixed margin albeit in the frequentist setup. Bayesian paradigm provides a natural path to integrate historical and current trials' information via sequential learning. In this paper, we propose a Bayesian approach for simultaneous testing of non-inferiority and assay sensitivity in a three-arm trial with normal responses. For the experimental arm, in absence of historical information, non-informative priors ar...

Research paper thumbnail of Bayesian nonparametric inference

Institute of Mathematical Statistics Lecture Notes - Monograph Series, 1992

Research paper thumbnail of CONVERGENCE OF DIRICHLET MEASURES AND THE INTERPRETATION OF THEIR PARAMETER11Research supported by the U.S. Army Research Office under Grant no. DAAG 29-79-C-0158. The United States Government is authorized to reproduce and distribute reprints for governmental purposes

Statistical Decision Theory and Related Topics III, 1982

The form of the Bayes estimate of the population mean with respect to a Dirichlet prior with para... more The form of the Bayes estimate of the population mean with respect to a Dirichlet prior with parameter a has given rise to the interpretation that a ( X ) is the prior sample size. Furthermore, if a ( X ) is made to tend to zero, then the Bayes estimate mathematically converges to the classical estimator, that is, the sample mean. This has further given rise to the general feeling that allowing a ( X ) to become small not only makes the prior sample size small but also that it corresponds to no prior information. By investigating the limits of prior distributions as the parameter a tends to various values, it is misleading to think of a ( X ) as the prior sample size and the smallness of a ( X ) as no prior information. In fact, very small values of a ( X ) actually mean that the prior has a lot of information concerning the unknown true distribution and is of a form that would be generally unacceptable to a statistician.

Research paper thumbnail of Assessing noninferiority in a three‐arm trial using the Bayesian approach

Statistics in Medicine, 2011

Non‐inferiority trials, which aim to demonstrate that a test product is not worse than a competit... more Non‐inferiority trials, which aim to demonstrate that a test product is not worse than a competitor by more than a pre‐specified small amount, are of great importance to the pharmaceutical community. As a result, methodology for designing and analyzing such trials is required, and developing new methods for such analysis is an important area of statistical research. The three‐arm trial consists of a placebo, a reference and an experimental treatment, and simultaneously tests the superiority of the reference over the placebo along with comparing this reference to an experimental treatment. In this paper, we consider the analysis of noninferiority trials using Bayesian methods which incorporate both parametric as well as semi‐parametric models. The resulting testing approach is both flexible and robust. The benefit of the proposed Bayesian methods is assessed via simulation, based on a study examining home‐based blood pressure interventions. Copyright © 2011 John Wiley & Sons, Ltd.

Research paper thumbnail of Modeling Population-Based Cancer Survival Trends Using Joinpoint Survival Models

In the United States cancer as a whole is the second leading cause of death and a major burden to... more In the United States cancer as a whole is the second leading cause of death and a major burden to health care, thus the medical progress against cancer is a major public health goal. There are many individ- ual studies to suggest that cancer treatment breakthroughs and early diagnosis have significantly improved the prognosis of cancer patients. To better understand

Research paper thumbnail of Nonparametric and Semiparametric Bayesian Reliability Analysis

Encyclopedia of Statistics in Quality and Reliability, 2008

Research paper thumbnail of Modelling Population-Based Cancer Survival Trends by using Join Point Models for Grouped Survival Data

Journal of the Royal Statistical Society Series A: Statistics in Society, 2009

SummaryIn the USA cancer as a whole is the second leading cause of death and a major burden to he... more SummaryIn the USA cancer as a whole is the second leading cause of death and a major burden to health care; thus medical progress against cancer is a major public health goal. There are many individual studies to suggest that cancer treatment breakthroughs and early diagnosis have significantly improved the prognosis of cancer patients. To understand better the relationship between medical improvements and the survival experience for the patient population at large, it is useful to evaluate cancer survival trends on the population level, e.g. to find out when and how much the cancer survival rates changed. We analyse population-based grouped cancer survival data by incorporating join points into the survival models. A join point survival model facilitates the identification of trends with significant change-points in cancer survival, when related to cancer treatments or interventions. The Bayesian information criterion is used to select the number of join points. The performance of ...

Research paper thumbnail of Nonparametric Bayes Estimation of Contamination Levels Using Observations from the Residual Distribution

Journal of the American Statistical Association, 2000

Research paper thumbnail of A Class of Semiparametric Mixture Cure Survival Models With Dependent Censoring

Journal of the American Statistical Association, 2009