James Stamey | Baylor University (original) (raw)
Papers by James Stamey
Advances and Applications in Statistics, 2021
Mixed treatment comparisons meta-analysis has become a popular methodology because of its ability... more Mixed treatment comparisons meta-analysis has become a popular methodology because of its ability to use separate trials to make comparisons about parameters, even when the parameters have not been directly compared. We consider a mixed treatment comparisons meta-analysis problem when analyzing Poisson data allowing for counts that are potentially underreported. Previously proposed methods do not allow for the presence of underreporting. Here, we illustrate how a constant underreporting rate for all treatments has no effect on relative risk comparisons; however, when the reporting rate changes with treatment, ignoring the underreporting can lead to considerable bias. We propose an approach that accounts for the underreporting and corrects for the bias.
Forest Products Journal, Mar 1, 2005
Four batches of commercially manufactured structural finger-jointed southern pine were examined t... more Four batches of commercially manufactured structural finger-jointed southern pine were examined to determine wood moisture content (MC) following a durability cycle. The three batches that gained moisture during the durability cycle had larger differences in MC between the wood pieces within the finger-jointed specimens. One batch lost moisture during the durability cycle and had greater uniformity in MC between the wood pieces within the finger-jointed specimens. Methodology that accounts for variability in MC between the wood pieces within finger-jointed specimens may need to be considered in durability cycle requirements specified in existing standards. Additionally, because similar vacuum-pressure-soak cycles precede durability strength tests and glueline delamination measurements, further work that examines the effect of differences in MC between the wood pieces within finger-jointed specimens on these tests may be warranted.
The South African …, 2008
Page 1. South African Statist. J. (2008) 42, 4764 47 BAYESIAN ESTIMATION OF A STANDARDIZED MORTA... more Page 1. South African Statist. J. (2008) 42, 4764 47 BAYESIAN ESTIMATION OF A STANDARDIZED MORTALITY RATIO WITH MISSING DEATH CERTIFICATES James D. Stamey, Dean M. Young & John W. Seaman jr. Department ...
The assumption of ‘no unmeasured confounders’ is a critical but unverifiable assumption required ... more The assumption of ‘no unmeasured confounders’ is a critical but unverifiable assumption required for causal inference yet quantitative sensitivity analyses to assess robustness of real-world evidence remains underutilized. The lack of use is likely in part due to complexity of implementation and often specific and restrictive data requirements required for application of each method. With the advent of sensitivity analyses methods that are broadly applicable in that they do not require identification of a specific unmeasured confounder – along with publicly available code for implementation – roadblocks toward broader use are decreasing. To spur greater application, here we present a best practice guidance to address the potential for unmeasured confounding at both the design and analysis stages, including a set of framing questions and an analytic toolbox for researchers. The questions at the design stage guide the research through steps evaluating the potential robustness of the d...
Epidemiology, Biostatistics, and Public Health
Purpose: The existence of unmeasured confounding can clearly undermine the validity of an observa... more Purpose: The existence of unmeasured confounding can clearly undermine the validity of an observational study. Methods of conducting sensitivity analyses to evaluate the impact of unmeasured confounding are well established. However, application of such methods to survival data (“time-to-event” outcomes) have received little attention in the literature. The purpose of this study is to propose a novel Bayesian method to account for unmeasured confounding for survival data. Methods: The Bayesian method is proposed under an assumption that the supplementary information on unmeasured confounding in the form of internal validation data, external validation data or expert elicited prior distributions is available. The method for incorporating such information to Cox proportional hazard model is described. Simulation studies are performed based on the recently published instrumental variable method to assess the impact of unmeasured confounding and to illustrate the improvement of the p...
Pharmacoepidemiology and drug safety, Jan 30, 2018
Observational pharmacoepidemiological studies can provide valuable information on the effectivene... more Observational pharmacoepidemiological studies can provide valuable information on the effectiveness or safety of interventions in the real world, but one major challenge is the existence of unmeasured confounder(s). While many analytical methods have been developed for dealing with this challenge, they appear under-utilized, perhaps due to the complexity and varied requirements for implementation. Thus, there is an unmet need to improve understanding the appropriate course of action to address unmeasured confounding under a variety of research scenarios. We implemented a stepwise search strategy to find articles discussing the assessment of unmeasured confounding in electronic literature databases. Identified publications were reviewed and characterized by the applicable research settings and information requirements required for implementing each method. We further used this information to develop a best practice recommendation to help guide the selection of appropriate analytical ...
PDA journal of pharmaceutical science and technology, Jan 27, 2016
For manufacturers of sterile drug products, steam sterilization is a common method used to provid... more For manufacturers of sterile drug products, steam sterilization is a common method used to provide assurance of the sterility of manufacturing equipment and products. The validation of sterilization processes is a regulatory requirement and relies upon the estimation of key resistance parameters of microorganisms. Traditional methods have relied upon point estimates for the resistance parameters. In this paper, we propose a Bayesian method for estimation of the well-known D_T, z, and F_o values that are used in the development and validation of sterilization processes. A Bayesian approach allows the uncertainty about these values to be modeled using probability distributions, thereby providing a fully risk-based approach to measures of sterility assurance. An example is given using the survivor curve and fraction negative methods for estimation of resistance parameters and we present a means by which a probabilistic conclusion can be made regarding the ability of a process to achiev...
Pharmacoepidemiology and drug safety, Sep 11, 2016
Observational studies are frequently used to assess the effectiveness of medical interventions in... more Observational studies are frequently used to assess the effectiveness of medical interventions in routine clinical practice. However, the use of observational data for comparative effectiveness is challenged by selection bias and the potential of unmeasured confounding. This is especially problematic for analyses using a health care administrative database, in which key clinical measures are often not available. This paper provides an approach to conducting a sensitivity analyses to investigate the impact of unmeasured confounding in observational studies. In a real world osteoporosis comparative effectiveness study, the bone mineral density (BMD) score, an important predictor of fracture risk and a factor in the selection of osteoporosis treatments, is unavailable in the data base and lack of baseline BMD could potentially lead to significant selection bias. We implemented Bayesian twin-regression models, which simultaneously model both the observed outcome and the unobserved unmea...
Journal of Biopharmaceutical Statistics, 2016
Validation of pharmaceutical manufacturing processes is a regulatory requirement and plays a key ... more Validation of pharmaceutical manufacturing processes is a regulatory requirement and plays a key role in the assurance of drug quality, safety, and efficacy. The FDA guidance on process validation recommends a life-cycle approach which involves process design, qualification, and verification. The European Medicines Agency makes similar recommendations. The main purpose of process validation is to establish scientific evidence that a process is capable of consistently delivering a quality product. A major challenge faced by manufacturers is the determination of the number of batches to be used for the qualification stage. In this paper we present a Bayesian assurance and sample size determination approach where prior process knowledge and data are used to determine the number of batches. An example is presented in which potency uniformity data is evaluated using a process capability metric. By using the posterior predictive distribution, we simulate qualification data and make a decision on the number of batches required for a desired level of assurance.
Journal of Biopharmaceutical Statistics
Statistical Methodology, 2010
We derive a new Bayesian credible interval estimator for comparing two Poisson rates when counts ... more We derive a new Bayesian credible interval estimator for comparing two Poisson rates when counts are underreported and an additional validation data set is available. We provide a closed-form posterior density for the difference between the two rates that yields insightful information on which prior parameters influence the posterior the most. We also apply the new interval estimator to a real-data example, investigate the performance of the credible interval, and examine the impact of informative priors on the rate difference posterior via ...
Statistica Neerlandica, 2011
Comparing occurrence rates of events of interest in science, business, and medicine is an importa... more Comparing occurrence rates of events of interest in science, business, and medicine is an important topic. Because count data are often under-reported, we desire to account for this error in the response when constructing interval estimators. In this article, we derive a Bayesian interval for the difference of two Poisson rates when counts are potentially under-reported. The under-reporting causes a lack of identifiability. Here, we use informative priors to construct a credible interval for the difference of two Poisson rate parameters with ...
Pharmaceutical Statistics, 2013
Unmeasured confounding is a common problem in observational studies. Failing to account for unmea... more Unmeasured confounding is a common problem in observational studies. Failing to account for unmeasured confounding can result in biased point estimators and poor performance of hypothesis tests and interval estimators. We provide examples of the impacts of unmeasured confounding on cost-effectiveness analyses using observational data along with a Bayesian approach to correct estimation. Assuming validation data are available, we propose a Bayesian approach to correct costeffectiveness studies for unmeasured confounding. We consider the cases where both cost and effectiveness are assumed to have a normal distribution and when costs are gamma distributed and effectiveness is normally distributed. Simulation studies were conducted to determine the impact of ignoring the unmeasured confounder and to determine the size of the validation data required to obtain valid inferences.
Pharmaceutical Statistics, 2013
Safety assessment is essential throughout medical product development. There has been increased a... more Safety assessment is essential throughout medical product development. There has been increased awareness of the importance of safety trials recently, in part due to recent US Food and Drug Administration guidance related to thorough assessment of cardiovascular risk in the treatment of type 2 diabetes. Bayesian methods provide great promise for improving the conduct of safety trials. In this paper, the safety subteam of the Drug Information Association Bayesian Scientific Working Group evaluates challenges associated with current methods for designing and analyzing safety trials and provides an overview of several suggested Bayesian opportunities that may increase efficiency of safety trials along with relevant case examples. Copyright
Nutrition, Metabolism and Cardiovascular Diseases, 2012
To determine whether and to what degree exposure to isoflavone-containing soy products affects EF... more To determine whether and to what degree exposure to isoflavone-containing soy products affects EF. Endothelial dysfunction has been identified as an independent coronary heart disease risk factor and a strong predictor of long-term cardiovascular morbidity and mortality. Data on the effects of exposure to isoflavone-containing soy products on EF are conflicting. A comprehensive literature search was conducted using the PUBMED database (National Library of Medicine, Bethesda, MD) inclusively through August 21, 2009 on RCTs using the keywords: soy, isoflavone, phytoestrogen, EF, flow mediated vasodilation, and FMD. A Bayesian meta-analysis was conducted to provide a comprehensive account of the effect of isoflavone-containing soy products on EF, as measured by FMD. A total of 17 RCTs were selected as having sufficient data for study inclusion. The overall mean absolute change in FMD (95% Bayesian CI) for isoflavone-containing soy product interventions was 1.15% (-0.52, 2.75). When the effects of separate interventions were considered, the treatment effect for isolated isoflavones was 1.98% (0.07, 3.97) compared to 0.72% (-1.39, 2.90) for isoflavone-containing soy protein. The models were not improved when considering study-specific effects such as cuff measurement location, prescribed dietary modification, and impaired baseline FMD. Cumulative evidence from the RCTs included in this meta-analysis indicates that exposure to soy isoflavones can modestly, but significantly, improve EF as measured by FMD. Therefore, exposure to isoflavone supplements may beneficially influence vascular health.
Journal of Statistical Planning and Inference, 2005
We formulate closed-form Bayesian estimators for two complementary Poisson rate parameters using ... more We formulate closed-form Bayesian estimators for two complementary Poisson rate parameters using double sampling with data subject to misclassification and error free data. We also derive closed-form Bayesian estimators for two misclassification parameters in the modified Poisson model we assume. We use our results to determine credible sets for the rate and misclassification parameters. Additionally, we use MCMC methods to determine Bayesian estimators for three or more rate parameters and the misclassification ...
Journal of Biopharmaceutical Statistics, 2013
In clinical trials, multiple outcomes are often collected in order to simultaneously assess effec... more In clinical trials, multiple outcomes are often collected in order to simultaneously assess effectiveness and safety. We develop a Bayesian procedure for determining the required sample size in a regression model where a continuous efficacy variable and a binary safety variable are observed. The sample size determination procedure is simulation based. The model accounts for correlation between the two variables. Through examples we demonstrate that savings in total sample size are possible when the correlation between these two variables is sufficiently high.
Computational Statistics & Data Analysis, 2012
Covariate misclassification is a common problem in epidemiology, genetics, and other biomedical a... more Covariate misclassification is a common problem in epidemiology, genetics, and other biomedical areas. Because this form of misclassification is known to bias estimators, accounting for it at the design stage is of high importance. In this paper, we extend on previous work applied to response misclassification by developing a Bayesian approach to sample size determination for a covariate misclassification model with no gold standard. Our procedure considers both conditionally independent tests and tests in which dependence exists between classifiers. We specifically consider a Bayesian power criterion for the sample size determination scheme, and we demonstrate the improvement in model power for our dual classifier approach compared to a naïve single classifier approach.
Communications in Statistics - Simulation and Computation, 2009
Positive predictive and negative predictive values (PPV and NPV) are often used to assess the acc... more Positive predictive and negative predictive values (PPV and NPV) are often used to assess the accuracy of binary diagnostic tests. Unlike sensitivity and specificity, PPV and NPV are functions of the accuracy of the test and the overall prevalence of the disease in the population. In many studies of performance of estimators of PPV and NPV the population prevalence is
Advances and Applications in Statistics, 2021
Mixed treatment comparisons meta-analysis has become a popular methodology because of its ability... more Mixed treatment comparisons meta-analysis has become a popular methodology because of its ability to use separate trials to make comparisons about parameters, even when the parameters have not been directly compared. We consider a mixed treatment comparisons meta-analysis problem when analyzing Poisson data allowing for counts that are potentially underreported. Previously proposed methods do not allow for the presence of underreporting. Here, we illustrate how a constant underreporting rate for all treatments has no effect on relative risk comparisons; however, when the reporting rate changes with treatment, ignoring the underreporting can lead to considerable bias. We propose an approach that accounts for the underreporting and corrects for the bias.
Forest Products Journal, Mar 1, 2005
Four batches of commercially manufactured structural finger-jointed southern pine were examined t... more Four batches of commercially manufactured structural finger-jointed southern pine were examined to determine wood moisture content (MC) following a durability cycle. The three batches that gained moisture during the durability cycle had larger differences in MC between the wood pieces within the finger-jointed specimens. One batch lost moisture during the durability cycle and had greater uniformity in MC between the wood pieces within the finger-jointed specimens. Methodology that accounts for variability in MC between the wood pieces within finger-jointed specimens may need to be considered in durability cycle requirements specified in existing standards. Additionally, because similar vacuum-pressure-soak cycles precede durability strength tests and glueline delamination measurements, further work that examines the effect of differences in MC between the wood pieces within finger-jointed specimens on these tests may be warranted.
The South African …, 2008
Page 1. South African Statist. J. (2008) 42, 4764 47 BAYESIAN ESTIMATION OF A STANDARDIZED MORTA... more Page 1. South African Statist. J. (2008) 42, 4764 47 BAYESIAN ESTIMATION OF A STANDARDIZED MORTALITY RATIO WITH MISSING DEATH CERTIFICATES James D. Stamey, Dean M. Young & John W. Seaman jr. Department ...
The assumption of ‘no unmeasured confounders’ is a critical but unverifiable assumption required ... more The assumption of ‘no unmeasured confounders’ is a critical but unverifiable assumption required for causal inference yet quantitative sensitivity analyses to assess robustness of real-world evidence remains underutilized. The lack of use is likely in part due to complexity of implementation and often specific and restrictive data requirements required for application of each method. With the advent of sensitivity analyses methods that are broadly applicable in that they do not require identification of a specific unmeasured confounder – along with publicly available code for implementation – roadblocks toward broader use are decreasing. To spur greater application, here we present a best practice guidance to address the potential for unmeasured confounding at both the design and analysis stages, including a set of framing questions and an analytic toolbox for researchers. The questions at the design stage guide the research through steps evaluating the potential robustness of the d...
Epidemiology, Biostatistics, and Public Health
Purpose: The existence of unmeasured confounding can clearly undermine the validity of an observa... more Purpose: The existence of unmeasured confounding can clearly undermine the validity of an observational study. Methods of conducting sensitivity analyses to evaluate the impact of unmeasured confounding are well established. However, application of such methods to survival data (“time-to-event” outcomes) have received little attention in the literature. The purpose of this study is to propose a novel Bayesian method to account for unmeasured confounding for survival data. Methods: The Bayesian method is proposed under an assumption that the supplementary information on unmeasured confounding in the form of internal validation data, external validation data or expert elicited prior distributions is available. The method for incorporating such information to Cox proportional hazard model is described. Simulation studies are performed based on the recently published instrumental variable method to assess the impact of unmeasured confounding and to illustrate the improvement of the p...
Pharmacoepidemiology and drug safety, Jan 30, 2018
Observational pharmacoepidemiological studies can provide valuable information on the effectivene... more Observational pharmacoepidemiological studies can provide valuable information on the effectiveness or safety of interventions in the real world, but one major challenge is the existence of unmeasured confounder(s). While many analytical methods have been developed for dealing with this challenge, they appear under-utilized, perhaps due to the complexity and varied requirements for implementation. Thus, there is an unmet need to improve understanding the appropriate course of action to address unmeasured confounding under a variety of research scenarios. We implemented a stepwise search strategy to find articles discussing the assessment of unmeasured confounding in electronic literature databases. Identified publications were reviewed and characterized by the applicable research settings and information requirements required for implementing each method. We further used this information to develop a best practice recommendation to help guide the selection of appropriate analytical ...
PDA journal of pharmaceutical science and technology, Jan 27, 2016
For manufacturers of sterile drug products, steam sterilization is a common method used to provid... more For manufacturers of sterile drug products, steam sterilization is a common method used to provide assurance of the sterility of manufacturing equipment and products. The validation of sterilization processes is a regulatory requirement and relies upon the estimation of key resistance parameters of microorganisms. Traditional methods have relied upon point estimates for the resistance parameters. In this paper, we propose a Bayesian method for estimation of the well-known D_T, z, and F_o values that are used in the development and validation of sterilization processes. A Bayesian approach allows the uncertainty about these values to be modeled using probability distributions, thereby providing a fully risk-based approach to measures of sterility assurance. An example is given using the survivor curve and fraction negative methods for estimation of resistance parameters and we present a means by which a probabilistic conclusion can be made regarding the ability of a process to achiev...
Pharmacoepidemiology and drug safety, Sep 11, 2016
Observational studies are frequently used to assess the effectiveness of medical interventions in... more Observational studies are frequently used to assess the effectiveness of medical interventions in routine clinical practice. However, the use of observational data for comparative effectiveness is challenged by selection bias and the potential of unmeasured confounding. This is especially problematic for analyses using a health care administrative database, in which key clinical measures are often not available. This paper provides an approach to conducting a sensitivity analyses to investigate the impact of unmeasured confounding in observational studies. In a real world osteoporosis comparative effectiveness study, the bone mineral density (BMD) score, an important predictor of fracture risk and a factor in the selection of osteoporosis treatments, is unavailable in the data base and lack of baseline BMD could potentially lead to significant selection bias. We implemented Bayesian twin-regression models, which simultaneously model both the observed outcome and the unobserved unmea...
Journal of Biopharmaceutical Statistics, 2016
Validation of pharmaceutical manufacturing processes is a regulatory requirement and plays a key ... more Validation of pharmaceutical manufacturing processes is a regulatory requirement and plays a key role in the assurance of drug quality, safety, and efficacy. The FDA guidance on process validation recommends a life-cycle approach which involves process design, qualification, and verification. The European Medicines Agency makes similar recommendations. The main purpose of process validation is to establish scientific evidence that a process is capable of consistently delivering a quality product. A major challenge faced by manufacturers is the determination of the number of batches to be used for the qualification stage. In this paper we present a Bayesian assurance and sample size determination approach where prior process knowledge and data are used to determine the number of batches. An example is presented in which potency uniformity data is evaluated using a process capability metric. By using the posterior predictive distribution, we simulate qualification data and make a decision on the number of batches required for a desired level of assurance.
Journal of Biopharmaceutical Statistics
Statistical Methodology, 2010
We derive a new Bayesian credible interval estimator for comparing two Poisson rates when counts ... more We derive a new Bayesian credible interval estimator for comparing two Poisson rates when counts are underreported and an additional validation data set is available. We provide a closed-form posterior density for the difference between the two rates that yields insightful information on which prior parameters influence the posterior the most. We also apply the new interval estimator to a real-data example, investigate the performance of the credible interval, and examine the impact of informative priors on the rate difference posterior via ...
Statistica Neerlandica, 2011
Comparing occurrence rates of events of interest in science, business, and medicine is an importa... more Comparing occurrence rates of events of interest in science, business, and medicine is an important topic. Because count data are often under-reported, we desire to account for this error in the response when constructing interval estimators. In this article, we derive a Bayesian interval for the difference of two Poisson rates when counts are potentially under-reported. The under-reporting causes a lack of identifiability. Here, we use informative priors to construct a credible interval for the difference of two Poisson rate parameters with ...
Pharmaceutical Statistics, 2013
Unmeasured confounding is a common problem in observational studies. Failing to account for unmea... more Unmeasured confounding is a common problem in observational studies. Failing to account for unmeasured confounding can result in biased point estimators and poor performance of hypothesis tests and interval estimators. We provide examples of the impacts of unmeasured confounding on cost-effectiveness analyses using observational data along with a Bayesian approach to correct estimation. Assuming validation data are available, we propose a Bayesian approach to correct costeffectiveness studies for unmeasured confounding. We consider the cases where both cost and effectiveness are assumed to have a normal distribution and when costs are gamma distributed and effectiveness is normally distributed. Simulation studies were conducted to determine the impact of ignoring the unmeasured confounder and to determine the size of the validation data required to obtain valid inferences.
Pharmaceutical Statistics, 2013
Safety assessment is essential throughout medical product development. There has been increased a... more Safety assessment is essential throughout medical product development. There has been increased awareness of the importance of safety trials recently, in part due to recent US Food and Drug Administration guidance related to thorough assessment of cardiovascular risk in the treatment of type 2 diabetes. Bayesian methods provide great promise for improving the conduct of safety trials. In this paper, the safety subteam of the Drug Information Association Bayesian Scientific Working Group evaluates challenges associated with current methods for designing and analyzing safety trials and provides an overview of several suggested Bayesian opportunities that may increase efficiency of safety trials along with relevant case examples. Copyright
Nutrition, Metabolism and Cardiovascular Diseases, 2012
To determine whether and to what degree exposure to isoflavone-containing soy products affects EF... more To determine whether and to what degree exposure to isoflavone-containing soy products affects EF. Endothelial dysfunction has been identified as an independent coronary heart disease risk factor and a strong predictor of long-term cardiovascular morbidity and mortality. Data on the effects of exposure to isoflavone-containing soy products on EF are conflicting. A comprehensive literature search was conducted using the PUBMED database (National Library of Medicine, Bethesda, MD) inclusively through August 21, 2009 on RCTs using the keywords: soy, isoflavone, phytoestrogen, EF, flow mediated vasodilation, and FMD. A Bayesian meta-analysis was conducted to provide a comprehensive account of the effect of isoflavone-containing soy products on EF, as measured by FMD. A total of 17 RCTs were selected as having sufficient data for study inclusion. The overall mean absolute change in FMD (95% Bayesian CI) for isoflavone-containing soy product interventions was 1.15% (-0.52, 2.75). When the effects of separate interventions were considered, the treatment effect for isolated isoflavones was 1.98% (0.07, 3.97) compared to 0.72% (-1.39, 2.90) for isoflavone-containing soy protein. The models were not improved when considering study-specific effects such as cuff measurement location, prescribed dietary modification, and impaired baseline FMD. Cumulative evidence from the RCTs included in this meta-analysis indicates that exposure to soy isoflavones can modestly, but significantly, improve EF as measured by FMD. Therefore, exposure to isoflavone supplements may beneficially influence vascular health.
Journal of Statistical Planning and Inference, 2005
We formulate closed-form Bayesian estimators for two complementary Poisson rate parameters using ... more We formulate closed-form Bayesian estimators for two complementary Poisson rate parameters using double sampling with data subject to misclassification and error free data. We also derive closed-form Bayesian estimators for two misclassification parameters in the modified Poisson model we assume. We use our results to determine credible sets for the rate and misclassification parameters. Additionally, we use MCMC methods to determine Bayesian estimators for three or more rate parameters and the misclassification ...
Journal of Biopharmaceutical Statistics, 2013
In clinical trials, multiple outcomes are often collected in order to simultaneously assess effec... more In clinical trials, multiple outcomes are often collected in order to simultaneously assess effectiveness and safety. We develop a Bayesian procedure for determining the required sample size in a regression model where a continuous efficacy variable and a binary safety variable are observed. The sample size determination procedure is simulation based. The model accounts for correlation between the two variables. Through examples we demonstrate that savings in total sample size are possible when the correlation between these two variables is sufficiently high.
Computational Statistics & Data Analysis, 2012
Covariate misclassification is a common problem in epidemiology, genetics, and other biomedical a... more Covariate misclassification is a common problem in epidemiology, genetics, and other biomedical areas. Because this form of misclassification is known to bias estimators, accounting for it at the design stage is of high importance. In this paper, we extend on previous work applied to response misclassification by developing a Bayesian approach to sample size determination for a covariate misclassification model with no gold standard. Our procedure considers both conditionally independent tests and tests in which dependence exists between classifiers. We specifically consider a Bayesian power criterion for the sample size determination scheme, and we demonstrate the improvement in model power for our dual classifier approach compared to a naïve single classifier approach.
Communications in Statistics - Simulation and Computation, 2009
Positive predictive and negative predictive values (PPV and NPV) are often used to assess the acc... more Positive predictive and negative predictive values (PPV and NPV) are often used to assess the accuracy of binary diagnostic tests. Unlike sensitivity and specificity, PPV and NPV are functions of the accuracy of the test and the overall prevalence of the disease in the population. In many studies of performance of estimators of PPV and NPV the population prevalence is