International Journal of Biostatistics最新文献_第5页

Efficient Nonparametric Causal Inference with Missing Exposure Information. 缺失暴露信息的有效非参数因果推理。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2020-03-14 DOI: 10.1515/ijb-2019-0087

Edward H Kennedy

{"title":"Efficient Nonparametric Causal Inference with Missing Exposure Information.","authors":"Edward H Kennedy","doi":"10.1515/ijb-2019-0087","DOIUrl":"https://doi.org/10.1515/ijb-2019-0087","url":null,"abstract":"Missing exposure information is a very common feature of many observational studies. Here we study identifiability and efficient estimation of causal effects on vector outcomes, in such cases where treatment is unconfounded but partially missing. We consider a missing at random setting where missingness in treatment can depend not only on complex covariates, but also on post-treatment outcomes. We give a new identifying expression for average treatment effects in this setting, along with the efficient influence function for this parameter in a nonparametric model, which yields a nonparametric efficiency bound. We use this latter result to construct nonparametric estimators that are less sensitive to the curse of dimensionality than usual, e. g. by having faster rates of convergence than the complex nuisance estimators they rely on. Further we show that these estimators can be root-n consistent and asymptotically normal under weak nonparametric conditions, even when constructed using flexible machine learning. Finally we apply these results to the problem of causal inference with a partially missing instrumental variable.","PeriodicalId":49058,"journal":{"name":"International Journal of Biostatistics","volume":"16 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2020-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/ijb-2019-0087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37737427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Bayesian Two-Stage Adaptive Design in Bioequivalence. 生物等效性中的贝叶斯两阶段自适应设计。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2019-07-16 DOI: 10.1515/ijb-2018-0105

Shengjie Liu, Jun Gao, Yuling Zheng, Lei Huang, Fangrong Yan

{"title":"Bayesian Two-Stage Adaptive Design in Bioequivalence.","authors":"Shengjie Liu, Jun Gao, Yuling Zheng, Lei Huang, Fangrong Yan","doi":"10.1515/ijb-2018-0105","DOIUrl":"https://doi.org/10.1515/ijb-2018-0105","url":null,"abstract":"Bioequivalence (BE) studies are an integral component of new drug development process, and play an important role in approval and marketing of generic drug products. However, existing design and evaluation methods are basically under the framework of frequentist theory, while few implements Bayesian ideas. Based on the bioequivalence predictive probability model and sample re-estimation strategy, we propose a new Bayesian two-stage adaptive design and explore its application in bioequivalence testing. The new design differs from existing two-stage design (such as Potvin's method B, C) in the following aspects. First, it not only incorporates historical information and expert information, but further combines experimental data flexibly to aid decision-making. Secondly, its sample re-estimation strategy is based on the ratio of the information in interim analysis to total information, which is simpler in calculation than the Potvin's method. Simulation results manifested that the two-stage design can be combined with various stop boundary functions, and the results are different. Moreover, the proposed method saves sample size compared to the Potvin's method under the conditions that type I error rate is below 0.05 and statistical power reaches 80 %.","PeriodicalId":49058,"journal":{"name":"International Journal of Biostatistics","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/ijb-2018-0105","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37156916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Simultaneous Inference of Treatment Effect Modification by Intermediate Response Endpoint Principal Strata with Application to Vaccine Trials. 中间反应终点主层对治疗效果改变的同时推断及其在疫苗试验中的应用。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2019-07-02 DOI: 10.1515/ijb-2018-0058

Yingying Zhuang, Ying Huang, Peter B Gilbert

{"title":"Simultaneous Inference of Treatment Effect Modification by Intermediate Response Endpoint Principal Strata with Application to Vaccine Trials.","authors":"Yingying Zhuang, Ying Huang, Peter B Gilbert","doi":"10.1515/ijb-2018-0058","DOIUrl":"https://doi.org/10.1515/ijb-2018-0058","url":null,"abstract":"In randomized clinical trials, researchers are often interested in identifying an inexpensive intermediate study endpoint (typically a biomarker) that is a strong effect modifier of the treatment effect on a longer-term clinical endpoint of interest. Motivated by randomized placebo-controlled preventive vaccine efficacy trials, within the principal stratification framework a pseudo-score type estimator has been proposed to estimate disease risks conditional on the counter-factual biomarker of interest under each treatment assignment to vaccine or placebo, yielding an estimator of biomarker conditional vaccine efficacy. This method can be used for trial designs that use baseline predictors of the biomarker and/or designs that vaccinate disease-free placebo recipients at the end of the trial. In this article, we utilize the pseudo-score estimator to estimate the biomarker conditional vaccine efficacy adjusting for baseline covariates. We also propose a perturbation resampling method for making simultaneous inference on conditional vaccine efficacy over the values of the biomarker. We illustrate our method with datasets from two phase 3 dengue vaccine efficacy trials.","PeriodicalId":49058,"journal":{"name":"International Journal of Biostatistics","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/ijb-2018-0058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37389087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Computationally Stable Estimation Procedure for the Multivariate Linear Mixed-Effect Model and Application to Malaria Public Health Problem. 多元线性混合效应模型的计算稳定估计方法及其在疟疾公共卫生问题中的应用

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2019-06-21 DOI: 10.1515/ijb-2017-0076

Eric Houngla Adjakossa, Norbert Mahouton Hounkonnou, Grégory Nuel

{"title":"Computationally Stable Estimation Procedure for the Multivariate Linear Mixed-Effect Model and Application to Malaria Public Health Problem.","authors":"Eric Houngla Adjakossa, Norbert Mahouton Hounkonnou, Grégory Nuel","doi":"10.1515/ijb-2017-0076","DOIUrl":"https://doi.org/10.1515/ijb-2017-0076","url":null,"abstract":"In this paper, we provide the ML (Maximum Likelihood) and the REML (REstricted ML) criteria for consistently estimating multivariate linear mixed-effects models with arbitrary correlation structure between the random effects across dimensions, but independent (and possibly heteroscedastic) residuals. By factorizing the random effects covariance matrix, we provide an explicit expression of the profiled deviance through a reparameterization of the model. This strategy can be viewed as the generalization of the estimation procedure used by Douglas Bates and his co-authors in the context of the fitting of one-dimensional linear mixed-effects models. Beside its robustness regarding the starting points, the approach enables a numerically consistent estimate of the random effects covariance matrix while classical alternatives such as the EM algorithm are usually non-consistent. In a simulation study, we compare the estimates obtained from the present method with the EM algorithm-based estimates. We finally apply the method to a study of an immune response to Malaria in Benin.","PeriodicalId":49058,"journal":{"name":"International Journal of Biostatistics","volume":"15 2","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/ijb-2017-0076","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37350619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Second Order Segmented Polynomials for Syphilis and Gonorrhea Prevalence and Incidence Trends Estimation: Application to Spectrum's Guinea-Bissau and South Africa Data. 梅毒和淋病流行和发病率趋势估计的二阶分段多项式:在Spectrum的几内亚比绍和南非数据中的应用。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2019-06-08 DOI: 10.1515/ijb-2017-0073

Severin Guy Mahiane, Carel Pretorius, Eline Korenromp

引用次数: 2

Simple Quasi-Bayes Approach for Modeling Mean Medical Costs. 平均医疗费用建模的简单拟贝叶斯方法。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2019-06-05 DOI: 10.1515/ijb-2018-0122

Grace Yoon, Wenxin Jiang, Lei Liu, Ya-Chen Tina Shih

{"title":"Simple Quasi-Bayes Approach for Modeling Mean Medical Costs.","authors":"Grace Yoon, Wenxin Jiang, Lei Liu, Ya-Chen Tina Shih","doi":"10.1515/ijb-2018-0122","DOIUrl":"https://doi.org/10.1515/ijb-2018-0122","url":null,"abstract":"AbstractSeveral statistical issues associated with health care costs, such as heteroscedasticity and severe skewness, make it challenging to estimate or predict medical costs. When the interest is modeling the mean cost, it is desirable to make no assumption on the density function or higher order moments. Another challenge in developing cost prediction models is the presence of many covariates, making it necessary to apply variable selection methods to achieve a balance of prediction accuracy and model simplicity. We propose Spike-or-Slab priors for Bayesian variable selection based on asymptotic normal estimates of the full model parameters that are consistent as long as the assumption on the mean cost is satisfied. In addition, the scope of model searching can be reduced by ranking the Z-statistics. This method possesses four advantages simultaneously: robust (due to avoiding assumptions on the density function or higher order moments), parsimonious (feature of variable selection), informative (due to its Bayesian flavor, which can compare posterior probabilities of candidate models) and efficient (by reducing model searching scope with the use of Z-ranking). We apply this method to the Medical Expenditure Panel Survey dataset.","PeriodicalId":49058,"journal":{"name":"International Journal of Biostatistics","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/ijb-2018-0122","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37325231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Semiparametric Inference for Proportional Mean Past Life Model. 比例平均过去寿命模型的半参数推断。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2019-05-18 DOI: 10.1515/ijb-2018-0020

Z Mansourvar, M Asadi

引用次数: 1

A Law of Large Numbers in the Supremum Norm for a Multiscale Stochastic Spatial Gene Network. 多尺度随机空间基因网络最高范数中的大数定律。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2019-05-15 DOI: 10.1515/ijb-2017-0091

Arnaud Debussche, Mac Jugal Nguepedja Nankep

引用次数: 5

Double Poisson-Tweedie Regression Models. 双泊松- tweedie回归模型。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2019-04-18 DOI: 10.1515/ijb-2018-0119

Ricardo R Petterle, Wagner H Bonat, Célestin C Kokonendji, Juliane C Seganfredo, Atamai Moraes, Monica G da Silva

{"title":"Double Poisson-Tweedie Regression Models.","authors":"Ricardo R Petterle, Wagner H Bonat, Célestin C Kokonendji, Juliane C Seganfredo, Atamai Moraes, Monica G da Silva","doi":"10.1515/ijb-2018-0119","DOIUrl":"https://doi.org/10.1515/ijb-2018-0119","url":null,"abstract":"In this paper, we further extend the recently proposed Poisson-Tweedie regression models to include a linear predictor for the dispersion as well as for the expectation of the count response variable. The family of the considered models is specified using only second-moments assumptions, where the variance of the count response has the form μ+ϕμp $mu + phi mu^p$, where µ is the expectation, ϕ and p are the dispersion and power parameters, respectively. Parameter estimations are carried out using an estimating function approach obtained by combining the quasi-score and Pearson estimating functions. The performance of the fitting algorithm is investigated through simulation studies. The results showed that our estimating function approach provides consistent estimators for both mean and dispersion parameters. The class of models is motivated by a data set concerning CD4 counting in HIV-positive pregnant women assisted in a public hospital in Curitiba, Paraná, Brazil. Specifically, we investigate the effects of a set of covariates in both expectation and dispersion structures. Our results showed that women living out of the capital Curitiba, with viral load equal or larger than 1000 copies and with previous diagnostic of HIV infection, present lower levels of CD4 cell count. Furthermore, we detected that the time to initiate the antiretroviral therapy decreases the data dispersion. The data set and R code are available as supplementary materials.","PeriodicalId":49058,"journal":{"name":"International Journal of Biostatistics","volume":"15 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/ijb-2018-0119","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37162937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Significance Tests for Boosted Location and Scale Models with Linear Base-Learners. 基于线性基础学习器的提升位置和比例模型的显著性检验。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2019-04-16 DOI: 10.1515/ijb-2018-0110

Tobias Hepp, Matthias Schmid, Andreas Mayr

{"title":"Significance Tests for Boosted Location and Scale Models with Linear Base-Learners.","authors":"Tobias Hepp, Matthias Schmid, Andreas Mayr","doi":"10.1515/ijb-2018-0110","DOIUrl":"https://doi.org/10.1515/ijb-2018-0110","url":null,"abstract":"Generalized additive models for location scale and shape (GAMLSS) offer very flexible solutions to a wide range of statistical analysis problems, but can be challenging in terms of proper model specification. This complex task can be simplified using regularization techniques such as gradient boosting algorithms, but the estimates derived from such models are shrunken towards zero and it is consequently not straightforward to calculate proper confidence intervals or test statistics. In this article, we propose two strategies to obtain p-values for linear effect estimates for Gaussian location and scale models based on permutation tests and a parametric bootstrap approach. These procedures can provide a solution for one of the remaining problems in the application of gradient boosting algorithms for distributional regression in biostatistical data analyses. Results from extensive simulations indicate that in low-dimensional data both suggested approaches are able to hold the type-I error threshold and provide reasonable test power comparable to the Wald-type test for maximum likelihood inference. In high-dimensional data, when gradient boosting is the only feasible inference for this model class, the power decreases but the type-I error is still under control. In addition, we demonstrate the application of both tests in an epidemiological study to analyse the impact of physical exercise on both average and the stability of the lung function of elderly people in Germany.","PeriodicalId":49058,"journal":{"name":"International Journal of Biostatistics","volume":"15 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/ijb-2018-0110","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37320864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8