Interval estimation of the risk ratio between a secondary infection, given a primary infection, and the primary infection.

Abstract:

:This paper discusses interval estimation of the risk ratio (RR) between a secondary infection, given a primary infection, and the primary infection. Three asymptotic closed-form interval estimators are developed using Wald's test statistic, the logarithmic transformation, and Fieller's theorem. The performance of these interval estimators is compared with respect to the coverage probability and the expected length of the resulting confidence intervals. When the underlying probability of a primary infection is high (say, 0.80), all three estimators perform reasonably well. In fact, in this case, they are all essentially equivalent when the number of subjects n > or = 100. When the probability of a primary infection is small (say, 0.20) or moderate (say, 0.30 to 0.50), the interval estimator using the logarithmic transformation outperforms the other two estimators when n < or = 100. In fact, the coverage probability of the former estimator is consistently greater than or equal to the desired confidence level in all the situations considered in this paper and hence is recommended for general use.

journal_name

Biometrics

journal_title

Biometrics

authors

Lui KJ

subject

Has Abstract

pub_date

1998-06-01 00:00:00

pages

706-11

issue

2

eissn

0006-341X

issn

1541-0420

journal_volume

54

pub_type

杂志文章
  • Locally efficient estimation of the quality-adjusted lifetime distribution with right-censored data and covariates.

    abstract::Zhao and Tsiatis (1997) consider the problem of estimation of the distribution of the quality-adjusted lifetime when the chronological survival time is subject to right censoring. The quality-adjusted lifetime is typically defined as a weighted sum of the times spent in certain states up until death or some other fail...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.0006-341x.1999.00530.x

    authors: van der Laan MJ,Hubbard A

    更新日期:1999-06-01 00:00:00

  • Multimodal neuroimaging data integration and pathway analysis.

    abstract::With advancements in technology, the collection of multiple types of measurements on a common set of subjects is becoming routine in science. Some notable examples include multimodal neuroimaging studies for the simultaneous investigation of brain structure and function and multi-omics studies for combining genetic an...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/biom.13351

    authors: Zhao Y,Li L,Caffo BS

    更新日期:2020-08-13 00:00:00

  • Estimating treatment effect in a proportional hazards model in randomized clinical trials with all-or-nothing compliance.

    abstract::We consider methods for estimating the treatment effect and/or the covariate by treatment interaction effect in a randomized clinical trial under noncompliance with time-to-event outcome. As in Cuzick et al. (2007), assuming that the patient population consists of three (possibly latent) subgroups based on treatment p...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/biom.12472

    authors: Li S,Gray RJ

    更新日期:2016-09-01 00:00:00

  • G-estimation and artificial censoring: problems, challenges, and applications.

    abstract::In principle, G-estimation is an attractive approach for dealing with confounding by variables affected by treatment. It has rarely been applied for estimation of the effects of treatment on failure-time outcomes. Part of this is due to artificial censoring, an analytic device which considers some subjects who actuall...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2011.01656.x

    authors: Joffe MM,Yang WP,Feldman H

    更新日期:2012-03-01 00:00:00

  • Regression analysis of case K interval-censored failure time data in the presence of informative censoring.

    abstract::Interval-censored failure time data occur in many fields such as demography, economics, medical research, and reliability and many inference procedures on them have been developed (Sun, 2006; Chen, Sun, and Peace, 2012). However, most of the existing approaches assume that the mechanism that yields interval censoring ...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/biom.12527

    authors: Wang P,Zhao H,Sun J

    更新日期:2016-12-01 00:00:00

  • Semiparametric maximum likelihood for nonlinear regression with measurement errors.

    abstract::This article demonstrates semiparametric maximum likelihood estimation of a nonlinear growth model for fish lengths using imprecisely measured ages. Data on the species corvina reina, found in the Gulf of Nicoya, Costa Rica, consist of lengths and imprecise ages for 168 fish and precise ages for a subset of 16 fish. T...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.0006-341x.2002.00448.x

    authors: Suh EY,Schafer DW

    更新日期:2002-06-01 00:00:00

  • The analysis of pair-matched case-control studies, a multivariate approach.

    abstract::In matched case-control studies one frequently must consider more than one variable in the analysis and in this paper a log-linear model is presented to meet this objective. A conditional argument yields a method for making inferences on the parameters measuring the association between the variables and disease. The r...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Holford TR

    更新日期:1978-12-01 00:00:00

  • To use or not to use? Backward equations in stochastic carcinogenesis models.

    abstract::The method based on the Kolmogorov backward equations of Little (1995, Biometrics 51, 1278-1291) for computing hazard functions for the multistage carcinogenesis models fails when model parameters are time-dependent. In addition to suggesting an alternative method based on the Kolmogorov forward equation, this note hi...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Zheng Q

    更新日期:1998-03-01 00:00:00

  • Variable selection for logistic regression using a prediction-focused information criterion.

    abstract::In biostatistical practice, it is common to use information criteria as a guide for model selection. We propose new versions of the focused information criterion (FIC) for variable selection in logistic regression. The FIC gives, depending on the quantity to be estimated, possibly different sets of selected variables....

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2006.00567.x

    authors: Claeskens G,Croux C,Van Kerckhoven J

    更新日期:2006-12-01 00:00:00

  • Nonparametric estimation of ROC curves in the absence of a gold standard.

    abstract::In the evaluation of diagnostic accuracy of tests, a gold standard on the disease status is required. However, in many complex diseases, it is impossible or unethical to obtain such a gold standard. If an imperfect standard is used, the estimated accuracy of the tests would be biased. This type of bias is called imper...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2005.00324.x

    authors: Zhou XH,Castelluccio P,Zhou C

    更新日期:2005-06-01 00:00:00

  • Binary regression analysis with pooled exposure measurements: a regression calibration approach.

    abstract::It has become increasingly common in epidemiological studies to pool specimens across subjects to achieve accurate quantitation of biomarkers and certain environmental chemicals. In this article, we consider the problem of fitting a binary regression model when an important exposure is subject to pooling. We take a re...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2010.01464.x

    authors: Zhang Z,Albert PS

    更新日期:2011-06-01 00:00:00

  • Capture-recapture estimation using finite mixtures of arbitrary dimension.

    abstract::Reversible jump Markov chain Monte Carlo (RJMCMC) methods are used to fit Bayesian capture-recapture models incorporating heterogeneity in individuals and samples. Heterogeneity in capture probabilities comes from finite mixtures and/or fixed sample effects allowing for interactions. Estimation by RJMCMC allows automa...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2009.01289.x

    authors: Arnold R,Hayakawa Y,Yip P

    更新日期:2010-06-01 00:00:00

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

    abstract::In epidemiologic studies, subjects are often misclassified as to their level of exposure. Ignoring this misclassification error in the analysis introduces bias in the estimates of certain parameters and invalidates many hypothesis tests. For situations in which there is misclassification of exposure in a follow-up stu...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Reade-Christopher SJ,Kupper LL

    更新日期:1991-06-01 00:00:00

  • Dynamic comparison of Kaplan-Meier proportions: monitoring a randomized clinical trial with a long-term binary endpoint.

    abstract::The approach to early termination for efficacy in a trial where events occur over time but the primary question of interest relates to a long-term binary endpoint is not straightforward. This article considers comparison of treatment groups with Kaplan-Meier (KM) proportions evaluated at increasing times from randomiz...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2007.00874.x

    authors: Brittain E,Follmann D,Yang S

    更新日期:2008-03-01 00:00:00

  • Regional spatial modeling of topsoil geochemistry.

    abstract::Geographic information about the levels of toxics in environmental media is commonly used in regional environmental health studies when direct measurements of personal exposure is limited or unavailable. In this article, we propose a statistical framework for analyzing the spatial distribution of topsoil geochemical p...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2008.01041.x

    authors: Calder CA,Craigmile PF,Zhang J

    更新日期:2009-03-01 00:00:00

  • On the accommodation of disease rate correlations in aggregate data studies of disease risk factors.

    abstract::Prentice and Sheppard (1995, Biometrika 82, 113-125) proposed a method for estimating relative risks associated with poorly measured exposures using disease rates from multiple populations and exposure and confounding factor data from sample surveys of persons in each population. The method involved an assumption of i...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Anderson AB,Prentice RL

    更新日期:1998-12-01 00:00:00

  • Improved dynamic predictions from joint models of longitudinal and survival data with time-varying effects using P-splines.

    abstract::In the field of cardio-thoracic surgery, valve function is monitored over time after surgery. The motivation for our research comes from a study which includes patients who received a human tissue valve in the aortic position. These patients are followed prospectively over time by standardized echocardiographic assess...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/biom.12814

    authors: Andrinopoulou ER,Eilers PHC,Takkenberg JJM,Rizopoulos D

    更新日期:2018-06-01 00:00:00

  • Extension of the rank sum test for clustered data: two-group comparisons with group membership defined at the subunit level.

    abstract::The Wilcoxon rank sum test is widely used for two-group comparisons for nonnormal data. An assumption of this test is independence of sampling units both between and within groups. In ophthalmology, data are often collected on two eyes of an individual, which are highly correlated. In ophthalmological clinical trials,...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2006.00582.x

    authors: Rosner B,Glynn RJ,Lee ML

    更新日期:2006-12-01 00:00:00

  • False discovery rate estimation for frequentist pharmacovigilance signal detection methods.

    abstract::Pharmacovigilance systems aim at early detection of adverse effects of marketed drugs. They maintain large spontaneous reporting databases for which several automatic signaling methods have been developed. One limit of those methods is that the decision rules for the signal generation are based on arbitrary thresholds...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2009.01262.x

    authors: Ahmed I,Dalmasso C,Haramburu F,Thiessard F,Broët P,Tubert-Bitter P

    更新日期:2010-03-01 00:00:00

  • A proposal for a goodness-of-fit test to the Arnason-Schwarz multisite capture-recapture model.

    abstract::In an analysis of capture-recapture data, the identification of a model that fits is a critical step. For the multisite (also called multistate) models used to analyze data gathered at several sites, no reliable test for assessing fit is currently available. We propose a test for the JMV model, a simple generalization...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/1541-0420.00006

    authors: Pradel R,Wintrebert CM,Gimenez O

    更新日期:2003-03-01 00:00:00

  • On assessing interrater agreement for multiple attribute responses.

    abstract::New methods are developed for assessing the extent of interrater agreement when each unit to be rated is characterized by a (possibly empty) subset of a specified set of distinct nominal attributes. For such multiple attribute response data, a two-rater concordance statistic is derived, and associated statistical infe...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Kupper LL,Hafner KB

    更新日期:1989-09-01 00:00:00

  • A proportional hazards model for multivariate interval-censored failure time data.

    abstract::This paper focuses on the methodology developed for analyzing a multivariate interval-censored data set from an AIDS observational study. A purpose of the study was to determine the natural history of the opportunistic infection cytomeglovirus (CMV) in an HIV-infected individual. For this observational study, laborato...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.0006-341x.2000.00940.x

    authors: Goggins WB,Finkelstein DM

    更新日期:2000-09-01 00:00:00

  • Sensitivity analysis: distributional assumptions and confounding assumptions.

    abstract::In a presentation of various methods for assessing the sensitivity of regression results to unmeasured confounding, Lin, Psaty, and Kronmal (1998, Biometrics54, 948-963) use a conditional independence assumption to derive algebraic relationships between the true exposure effect and the apparent exposure effect in a re...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2008.01024.x

    authors: Vanderweele TJ

    更新日期:2008-06-01 00:00:00

  • Evaluating multiple diagnostic tests with partial verification.

    abstract::To evaluate diagnostic tests, one would ideally like to verify, for example, with a biopsy, the disease state of all subjects in a study. Often, however, no all subjects are verified. Previous methods for evaluation assume that the decision to verify depends only on recorded variables. Sometimes, particularly if the d...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Baker SG

    更新日期:1995-03-01 00:00:00

  • Multievent: an extension of multistate capture-recapture models to uncertain states.

    abstract::Capture-recapture models were originally developed to account for encounter probabilities that are less than 1 in free-ranging animal populations. Nowadays, these models can deal with the movement of animals between different locations and are also used to study transitions between different states. However, their use...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2005.00318.x

    authors: Pradel R

    更新日期:2005-06-01 00:00:00

  • Spatial regression and spillover effects in cluster randomized trials with count outcomes.

    abstract::This paper describes methodology for analyzing data from cluster randomized trials with count outcomes, taking indirect effects as well spatial effects into account. Indirect effects are modeled using a novel application of a measure of depth within the intervention arm. Both direct and indirect effects can be estimat...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/biom.13316

    authors: Anaya-Izquierdo K,Alexander N

    更新日期:2020-06-18 00:00:00

  • A Bayesian approach to the analysis of quantal bioassay studies using nonparametric mixture models.

    abstract::We develop a Bayesian nonparametric mixture modeling framework for quantal bioassay settings. The approach is built upon modeling dose-dependent response distributions. We adopt a structured nonparametric prior mixture model, which induces a monotonicity restriction for the dose-response curve. Particular emphasis is ...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/biom.12120

    authors: Fronczyk K,Kottas A

    更新日期:2014-03-01 00:00:00

  • Modeling adverse birth outcomes via confirmatory factor quantile regression.

    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

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2011.01639.x

    authors: Burgette LF,Reiter JP

    更新日期:2012-03-01 00:00:00

  • Survival estimation using splines.

    abstract::A nonparametric maximum likelihood procedure is given for estimating the survivor function from right-censored data. It approximates the hazard rate by a simple function such as a spline, with different approximations yielding different estimators. A special case is that proposed by Nelson (1969, Journal of Quality Te...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Whittemore AS,Keller JB

    更新日期:1986-09-01 00:00:00

  • Dynamic analysis of multivariate failure time data.

    abstract::We present an approach for analyzing internal dependencies in counting processes. This covers the case with repeated events on each of a number of individuals, and more generally, the situation where several processes are observed for each individual. We define dynamic covariates, i.e., covariates depending on the pas...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.0006-341X.2004.00227.x

    authors: Aalen OO,Fosen J,Weedon-Fekjaer H,Borgan O,Husebye E

    更新日期:2004-09-01 00:00:00