Effects of exposure misclassification on regression analyses of epidemiologic follow-up study data.

abstract：:An individual's health condition can affect the frequency and intensity of episodes that can occur repeatedly and that may be related to an event time of interest. For example, bleeding episodes during pregnancy may indicate problems predictive of preterm delivery. Motivated by this application, we propose a joint mod...

journal_title：Biometrics

authors： Herring AH,Yang J

更新日期：2007-06-01 00:00:00

abstract：:As ultra high-dimensional longitudinal data are becoming ever more apparent in fields such as public health and bioinformatics, developing flexible methods with a sparse model is of high interest. In this setting, the dimension of the covariates can potentially grow exponentially as ...

journal_title：Biometrics

authors： Green B,Lian H,Yu Y,Zu T

更新日期：2020-08-04 00:00:00

abstract：:Motivated by the spatial modeling of aberrant crypt foci (ACF) in colon carcinogenesis, we consider binary data with probabilities modeled as the sum of a nonparametric mean plus a latent Gaussian spatial process that accounts for short-range dependencies. The mean is modeled in a general way using regression splines....

journal_title：Biometrics

authors： Apanasovich TV,Ruppert D,Lupton JR,Popovic N,Turner ND,Chapkin RS,Carroll RJ

更新日期：2008-06-01 00:00:00

abstract：:Complex issues arise when investigating the association between longitudinal immunologic measures and time to an event, such as time to relapse, in cancer vaccine trials. Unlike many clinical trials, we may encounter patients who are cured and no longer susceptible to the time-to-event endpoint. If there are cured pat...

journal_title：Biometrics

authors： Brown ER,Ibrahim JG

更新日期：2003-09-01 00:00:00

abstract：:Quantitative traits analyzed in Genome-Wide Association Studies (GWAS) are often nonnormally distributed. For such traits, association tests based on standard linear regression are subject to reduced power and inflated type I error in finite samples. Applying the rank-based inverse normal transformation (INT) to nonno...

journal_title：Biometrics

authors： McCaw ZR,Lane JM,Saxena R,Redline S,Lin X

更新日期：2020-12-01 00:00:00

abstract：:In controlled clinical trials there are usually several prognostic factors known or thought to influence the patient's ability to respond to treatment. Therefore, the method of sequential treatment assignment needs to be designed so that treatment balance is simultaneously achieved across all such patients factor. Tra...

journal_title：Biometrics

authors： Pocock SJ,Simon R

更新日期：1975-03-01 00:00:00

abstract：:Often with data from immunoassays, the concentration-response relationship is nonlinear and intra-assay response variance is heterogeneous. Estimation of the standard curve is usually based on a nonlinear heteroscedastic regression model for concentration-response, where variance is modeled as a function of mean respo...

journal_title：Biometrics

authors： Belanger BA,Davidian M,Giltinan DM

更新日期：1996-03-01 00:00:00

abstract：:Large amounts of longitudinal health records are now available for dynamic monitoring of the underlying processes governing the observations. However, the health status progression across time is not typically observed directly: records are observed only when a subject interacts with the system, yielding irregular and...

journal_title：Biometrics

authors： Luo Y,Stephens DA,Verma A,Buckeridge DL

更新日期：2020-03-11 00:00:00

abstract：:In this article, we present new methods to analyze data from an experiment using rodent models to investigate the role of p27, an important cell-cycle mediator, in early colon carcinogenesis. The responses modeled here are essentially functions nested within a two-stage hierarchy. Standard functional data analysis lit...

journal_title：Biometrics

authors： Baladandayuthapani V,Mallick BK,Young Hong M,Lupton JR,Turner ND,Carroll RJ

更新日期：2008-03-01 00:00:00

abstract：:Advances in sequencing technologies and bioinformatics tools have vastly improved our ability to collect and analyze data from complex microbial communities. A major goal of microbiome studies is to correlate the overall microbiome composition with clinical or environmental variables. La Rosa et al. recently proposed ...

journal_title：Biometrics

authors： Song Y,Zhao H,Wang T

更新日期：2020-06-01 00:00:00

abstract：:Consider a collection of spatially clustered objects where the clusters are geographically rare. Of interest is estimation of the total number of objects on the site from a sample of plots of equal size. Under these spatial conditions, adaptive cluster sampling of plots is generally useful in improving efficiency in e...

journal_title：Biometrics

authors： Christman MC,Pontius JS

更新日期：2000-06-01 00:00:00

abstract：:We extend the Mantel-Haenszel estimating function to estimate both the intra-cluster pairwise correlation and the main effects for sparse clustered binary data. We propose both a composite likelihood approach and an estimating function approach for the analysis of such data. The proposed estimators are consistent and ...

journal_title：Biometrics

authors： Wang M,Williamson JM

更新日期：2005-12-01 00:00:00

abstract：:Phase I trials to study the pharmacokinetic properties of a new drug generally involve a restricted number of healthy volunteers. Because of the nature of the group involved in such studies, the appropriate distributional assumptions are not always obvious. These model assumptions include the actual distribution but a...

journal_title：Biometrics

authors： Lindsey JK,Byrom WD,Wang J,Jarvis P,Jones B

更新日期：2000-03-01 00:00:00

abstract：:Diggle and Kenward (1994, Applied Statistics 43, 49-93) proposed a selection model for continuous longitudinal data subject to nonrandom dropout. It has provoked a large debate about the role for such models. The original enthusiasm was followed by skepticism about the strong but untestable assumptions on which this t...

journal_title：Biometrics

authors： Verbeke G,Molenberghs G,Thijs H,Lesaffre E,Kenward MG

更新日期：2001-03-01 00:00:00

abstract：:Logistic regression is a popular tool for risk analysis in medical and population health science. With continuous response data, it is common to create a dichotomous outcome for logistic regression analysis by specifying a threshold for positivity. Fitting a linear regression to the nondichotomized response variable a...

journal_title：Biometrics

authors： Schörgendorfer A,Branscum AJ,Hanson TE

更新日期：2013-06-01 00:00:00

abstract：:In the context of group testing screening, McMahan, Tebbs, and Bilder (2012, Biometrics 68, 287-296) proposed a two-stage procedure in a heterogenous population in the presence of misclassification. In earlier work published in Biometrics, Kim, Hudgens, Dreyfuss, Westreich, and Pilcher (2007, Biometrics 63, 1152-1162)...

journal_title：Biometrics

authors： Malinovsky Y,Albert PS,Roy A

更新日期：2016-03-01 00:00:00

abstract：:Some covariate-adaptive randomization methods have been used in clinical trials for a long time, but little theoretical work has been done about testing hypotheses under covariate-adaptive randomization until Shao et al. (2010) who provided a theory with detailed discussion for responses under linear models. In this a...

journal_title：Biometrics

authors： Shao J,Yu X

更新日期：2013-12-01 00:00:00

abstract：:We describe a Bayesian quantile regression model that uses a confirmatory factor structure for part of the design matrix. This model is appropriate when the covariates are indicators of scientifically determined latent factors, and it is these latent factors that analysts seek to include as predictors in the quantile ...

journal_title：Biometrics

authors： Burgette LF,Reiter JP

更新日期：2012-03-01 00:00:00

abstract：:In this study we are concerned with the construction of confidence intervals for the conditional probability of misallocation associated with Anderson's classification statistics, W. The available methods of computing confidence intervals for the conditional probability are not satisfactory in practice, mainly because...

journal_title：Biometrics

authors： McLachlan GJ

更新日期：1975-03-01 00:00:00

abstract：:The classical concordance correlation coefficient (CCC) to measure agreement among a set of observers assumes data to be distributed as normal and a linear relationship between the mean and the subject and observer effects. Here, the CCC is generalized to afford any distribution from the exponential family by means of...

journal_title：Biometrics

authors： Carrasco JL

更新日期：2010-09-01 00:00:00

abstract：:A multiple toxicity model for the quantal response of organisms is constructed based on an existing bivariate theory. The main assumption is that the tolerances follow a multivariate normal distribution function. However, any monotone tolerance distribution can be applied by mapping the integration region in the n-dim...

journal_title：Biometrics

authors： Christensen ER,Chen CY

更新日期：1985-09-01 00:00:00

abstract：:We describe group sequential tests for a bivariate response. The tests are defined in terms of the two response components jointly, rather than through a single summary statistic. Such methods are appropriate when the two responses concern different aspects of a treatment; for example, one might wish to show that a ne...

journal_title：Biometrics

authors： Jennison C,Turnbull BW

更新日期：1993-09-01 00:00:00

abstract：:A log-linear model for estimating the size of a closed population is defined for inverse multiple-recapture sampling with dependent samples. Efficient estimators of the log-linear model parameters and the population size are obtained by the method of minimum chi-square. A chi-square test of the general linear hypothes...

journal_title：Biometrics

authors： Bonett DG,Woodward JA,Bentler PM

更新日期：1987-12-01 00:00:00

abstract：:We consider hidden Markov models as a versatile class of models for weakly dependent random phenomena. The topic of the present paper is likelihood-ratio testing for hidden Markov models, and we show that, under appropriate conditions, the standard asymptotic theory of likelihood-ratio tests is valid. Such tests are c...

journal_title：Biometrics

authors： Giudici P,Rydén T,Vandekerkhove P

更新日期：2000-09-01 00:00:00

abstract：:Image-on-image regression analysis, using images to predict images, is a challenging task, due to (1) the high dimensionality and (2) the complex spatial dependence structures in image predictors and image outcomes. In this work, we propose a novel image-on-image regression model, by extending a spatial Bayesian laten...

journal_title：Biometrics

authors： Guo C,Kang J,Johnson TD

更新日期：2020-12-27 00:00:00

abstract：:Many statistical tests have been proposed for case-control data to detect disease association with multiple single nucleotide polymorphisms (SNPs) in linkage disequilibrium. The main reason for the existence of so many tests is that each test aims to detect one or two aspects of many possible distributional difference...

journal_title：Biometrics

authors： Han F,Pan W

更新日期：2012-03-01 00:00:00

abstract：:Matched case-control designs are commonly used in epidemiologic studies for increased efficiency. These designs have recently been introduced to the setting of modern imaging and genomic studies, which are characterized by high-dimensional covariates. However, appropriate statistical analyses that adjust for the match...

journal_title：Biometrics

authors： Qian J,Payabvash S,Kemmling A,Lev MH,Schwamm LH,Betensky RA

更新日期：2014-03-01 00:00:00

abstract：:A Bayesian multivariate adaptive regression spline fitting approach is used to model univariate and multivariate survival data with censoring. The possible models contain the proportional hazards model as a subclass and automatically detect departures from this. A reversible jump Markov chain Monte Carlo algorithm is ...

journal_title：Biometrics

authors： Mallick BK,Denison DG,Smith AF

更新日期：1999-12-01 00:00:00

abstract：:We consider inference for the reaction rates in discretely observed networks such as those found in models for systems biology, population ecology, and epidemics. Most such networks are neither slow enough nor small enough for inference via the true state-dependent Markov jump process to be feasible. Typically, infere...

journal_title：Biometrics

authors： Fearnhead P,Giagos V,Sherlock C

更新日期：2014-06-01 00:00:00

abstract：:In large cohort studies, it often happens that some covariates are expensive to measure and hence only measured on a validation set. On the other hand, relatively cheap but error-prone measurements of the covariates are available for all subjects. Regression calibration (RC) estimation method (Prentice, 1982, Biometri...

journal_title：Biometrics

authors： Yu M,Nan B

更新日期：2010-06-01 00:00:00