International Journal of Biostatistics最新文献_第2页

Prediction-based variable selection for component-wise gradient boosting. 基于预测的梯度增强变量选择。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2023-11-27 eCollection Date: 2024-05-01 DOI: 10.1515/ijb-2023-0052

Sophie Potts, Elisabeth Bergherr, Constantin Reinke, Colin Griesbach

引用次数: 0

Bayesian second-order sensitivity of longitudinal inferences to non-ignorability: an application to antidepressant clinical trial data. 纵向推论对不可忽略性的贝叶斯二阶敏感性:抗抑郁药临床试验数据的应用。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2023-11-27 eCollection Date: 2024-11-01 DOI: 10.1515/ijb-2022-0014

Elahe Momeni Roochi, Samaneh Eftekhari Mahabadi

{"title":"Bayesian second-order sensitivity of longitudinal inferences to non-ignorability: an application to antidepressant clinical trial data.","authors":"Elahe Momeni Roochi, Samaneh Eftekhari Mahabadi","doi":"10.1515/ijb-2022-0014","DOIUrl":"10.1515/ijb-2022-0014","url":null,"abstract":"Incomplete data is a prevalent complication in longitudinal studies due to individuals' drop-out before intended completion time. Currently available methods via commercial software for analyzing incomplete longitudinal data at best rely on the ignorability of the drop-outs. If the underlying missing mechanism was non-ignorable, potential bias arises in the statistical inferences. To remove the bias when the drop-out is non-ignorable, joint complete-data and drop-out models have been proposed which involve computational difficulties and untestable assumptions. Since the critical ignorability assumption is unverifiable based on the observed part of the sample, some local sensitivity indices have been proposed in the literature. Specifically, Eftekhari Mahabadi (Second-order local sensitivity to non-ignorability in Bayesian inferences. Stat Med 2018;59:55-95) proposed a second-order local sensitivity tool for Bayesian analysis of cross-sectional studies and show its better performance for handling bias compared with the first-order ones. In this paper, we aim to extend this index for the Bayesian sensitivity analysis of normal longitudinal studies with drop-outs. The index is driven based on a selection model for the drop-out mechanism and a Bayesian linear mixed-effect complete-data model. The presented formulas are calculated using the posterior estimation and draws from the simpler ignorable model. The method is illustrated via some simulation studies and sensitivity analysis of a real antidepressant clinical trial data. Overall, the numerical analysis showed that when repeated outcomes are subject to missingness, regression coefficient estimates are nearly approximated well by a linear function in the neighbourhood of MAR model, but there are a considerable amount of second-order sensitivity for the error term and random effect variances in Bayesian linear mixed-effect model framework.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":" ","pages":"599-629"},"PeriodicalIF":1.2,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138441586","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

Revisiting incidence rates comparison under right censorship. 在正确的审查制度下重温发病率比较。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2023-11-14 eCollection Date: 2024-11-01 DOI: 10.1515/ijb-2023-0025

Pablo Martínez-Camblor, Susana Díaz-Coto

引用次数: 0

Frontmatter 头版头条

4区数学

International Journal of Biostatistics Pub Date : 2023-11-01 DOI: 10.1515/ijb-2023-frontmatter2

引用次数: 0

Testing for association between ordinal traits and genetic variants in pedigree-structured samples by collapsing and kernel methods. 通过折叠和核方法测试系谱结构样本中序数性状和遗传变异之间的关联。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2023-09-26 eCollection Date: 2024-11-01 DOI: 10.1515/ijb-2022-0123

Li-Chu Chien

{"title":"Testing for association between ordinal traits and genetic variants in pedigree-structured samples by collapsing and kernel methods.","authors":"Li-Chu Chien","doi":"10.1515/ijb-2022-0123","DOIUrl":"10.1515/ijb-2022-0123","url":null,"abstract":"In genome-wide association studies (GWAS), logistic regression is one of the most popular analytics methods for binary traits. Multinomial regression is an extension of binary logistic regression that allows for multiple categories. However, many GWAS methods have been limited application to binary traits. These methods have improperly often been used to account for ordinal traits, which causes inappropriate type I error rates and poor statistical power. Owing to the lack of analysis methods, GWAS of ordinal traits has been known to be problematic and gaining attention. In this paper, we develop a general framework for identifying ordinal traits associated with genetic variants in pedigree-structured samples by collapsing and kernel methods. We use the local odds ratios GEE technology to account for complicated correlation structures between family members and ordered categorical traits. We use the retrospective idea to treat the genetic markers as random variables for calculating genetic correlations among markers. The proposed genetic association method can accommodate ordinal traits and allow for the covariate adjustment. We conduct simulation studies to compare the proposed tests with the existing models for analyzing the ordered categorical data under various configurations. We illustrate application of the proposed tests by simultaneously analyzing a family study and a cross-sectional study from the Genetic Analysis Workshop 19 (GAW19) data.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":" ","pages":"677-690"},"PeriodicalIF":1.2,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41177324","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

Frontmatter 头版头条

4区数学

International Journal of Biostatistics Pub Date : 2023-05-01 DOI: 10.1515/ijb-2023-frontmatter1

引用次数: 0

Approximate reciprocal relationship between two cause-specific hazard ratios in COVID-19 data with mutually exclusive events 在具有互斥事件的COVID-19数据中，两个病因特异性风险比之间存在近似的倒数关系

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2021-04-27 DOI: 10.1101/2021.04.22.21255955

Wentian Li, S. Cetin, A. Ulgen, M. Cetin, Hakan Şıvgın, Yaning Yang

{"title":"Approximate reciprocal relationship between two cause-specific hazard ratios in COVID-19 data with mutually exclusive events","authors":"Wentian Li, S. Cetin, A. Ulgen, M. Cetin, Hakan Şıvgın, Yaning Yang","doi":"10.1101/2021.04.22.21255955","DOIUrl":"https://doi.org/10.1101/2021.04.22.21255955","url":null,"abstract":"Abstract COVID-19 survival data presents a special situation where not only the time-to-event period is short, but also the two events or outcome types, death and release from hospital, are mutually exclusive, leading to two cause-specific hazard ratios (csHR d and csHR r ). The eventual mortality/release outcome is also analyzed by logistic regression to obtain odds-ratio (OR). We have the following three empirical observations: (1) The magnitude of OR is an upper limit of the csHR d : |log(OR)| ≥ |log(csHR d )|. This relationship between OR and HR might be understood from the definition of the two quantities; (2) csHR d and csHR r point in opposite directions: log(csHR d ) ⋅ log(csHR r ) < 0; This relation is a direct consequence of the nature of the two events; and (3) there is a tendency for a reciprocal relation between csHR d and csHR r : csHR d ∼ 1/csHR r . Though an approximate reciprocal trend between the two hazard ratios is in indication that the same factor causing faster death also lead to slow recovery by a similar mechanism, and vice versa, a quantitative relation between csHR d and csHR r in this context is not obvious. These results may help future analyses of data from COVID-19 or other similar diseases, in particular if the deceased patients are lacking, whereas surviving patients are abundant.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":"0 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42193520","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

Asymptotic properties of the two one-sided t-tests – new insights and the Schuirmann-constant 两个单侧t检验的渐近性质——新见解和Schuirmann常数

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2021-01-08 DOI: 10.1515/IJB-2020-0057

Christian Palmes, Tobias Bluhmki, Benedikt Funke, E. Bluhmki

{"title":"Asymptotic properties of the two one-sided t-tests – new insights and the Schuirmann-constant","authors":"Christian Palmes, Tobias Bluhmki, Benedikt Funke, E. Bluhmki","doi":"10.1515/IJB-2020-0057","DOIUrl":"https://doi.org/10.1515/IJB-2020-0057","url":null,"abstract":"Abstract The two one-sided t-tests (TOST) method is the most popular statistical equivalence test with many areas of application, i.e., in the pharmaceutical industry. Proper sample size calculation is needed in order to show equivalence with a certain power. Here, the crucial problem of choosing a suitable mean-difference in TOST sample size calculations is addressed. As an alternative concept, it is assumed that the mean-difference follows an a-priori distribution. Special interest is given to the uniform and some centered triangle a-priori distributions. Using a newly developed asymptotical theory a helpful analogy principle is found: every a-priori distribution corresponds to a point mean-difference, which we call its Schuirmann-constant. This constant does not depend on the standard deviation and aims to support the investigator in finding a well-considered mean-difference for proper sample size calculations in complex data situations. In addition to the proposed concept, we demonstrate that well-known sample size approximation formulas in the literature are in fact biased and state their unbiased corrections as well. Moreover, an R package is provided for a right away application of our newly developed concepts.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":"18 1","pages":"19 - 38"},"PeriodicalIF":1.2,"publicationDate":"2021-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/IJB-2020-0057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46667419","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: 1

Estimation of semi-Markov multi-state models: a comparison of the sojourn times and transition intensities approaches 半马尔可夫多状态模型的估计:逗留时间和转移强度方法的比较

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2020-05-29 DOI: 10.1515/IJB-2020-0083

A. Asanjarani, B. Liquet, Y. Nazarathy

{"title":"Estimation of semi-Markov multi-state models: a comparison of the sojourn times and transition intensities approaches","authors":"A. Asanjarani, B. Liquet, Y. Nazarathy","doi":"10.1515/IJB-2020-0083","DOIUrl":"https://doi.org/10.1515/IJB-2020-0083","url":null,"abstract":"Abstract Semi-Markov models are widely used for survival analysis and reliability analysis. In general, there are two competing parameterizations and each entails its own interpretation and inference properties. On the one hand, a semi-Markov process can be defined based on the distribution of sojourn times, often via hazard rates, together with transition probabilities of an embedded Markov chain. On the other hand, intensity transition functions may be used, often referred to as the hazard rates of the semi-Markov process. We summarize and contrast these two parameterizations both from a probabilistic and an inference perspective, and we highlight relationships between the two approaches. In general, the intensity transition based approach allows the likelihood to be split into likelihoods of two-state models having fewer parameters, allowing efficient computation and usage of many survival analysis tools. Nevertheless, in certain cases the sojourn time based approach is natural and has been exploited extensively in applications. In contrasting the two approaches and contemporary relevant R packages used for inference, we use two real datasets highlighting the probabilistic and inference properties of each approach. This analysis is accompanied by an R vignette.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":"18 1","pages":"243 - 262"},"PeriodicalIF":1.2,"publicationDate":"2020-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/IJB-2020-0083","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43491644","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: 14

Incorporating Contact Network Uncertainty in Individual Level Models of Infectious Disease using Approximate Bayesian Computation 用近似贝叶斯计算纳入传染病个体水平模型中的接触网络不确定性

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2019-12-10 DOI: 10.1515/ijb-2017-0092

Waleed Almutiry, R. Deardon

引用次数: 7