International Journal of Biostatistics最新文献_第7页

A parametric approach to relaxing the independence assumption in relative survival analysis. 放宽相对生存分析中独立性假设的参数化方法。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2022-11-01 DOI: 10.1515/ijb-2021-0016

Reuben Adatorwovor, Aurelien Latouche, Jason P Fine

{"title":"A parametric approach to relaxing the independence assumption in relative survival analysis.","authors":"Reuben Adatorwovor, Aurelien Latouche, Jason P Fine","doi":"10.1515/ijb-2021-0016","DOIUrl":"https://doi.org/10.1515/ijb-2021-0016","url":null,"abstract":"With known cause of death (CoD), competing risk survival methods are applicable in estimating disease-specific survival. Relative survival analysis may be used to estimate disease-specific survival when cause of death is either unknown or subject to misspecification and not reliable for practical usage. This method is popular for population-based cancer survival studies using registry data and does not require CoD information. The standard estimator is the ratio of all-cause survival in the cancer cohort group to the known expected survival from a general reference population. Disease-specific death competes with other causes of mortality, potentially creating dependence among the CoD. The standard ratio estimate is only valid when death from disease and death from other causes are independent. To relax the independence assumption, we formulate dependence using a copula-based model. Likelihood-based parametric method is used to fit the distribution of disease-specific death without CoD information, where the copula is assumed known and the distribution of other cause of mortality is derived from the reference population. We propose a sensitivity analysis, where the analysis is conducted across a range of assumed dependence structures. We demonstrate the utility of our method through simulation studies and an application to French breast cancer data.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10485972","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

An improved method for analysis of interrupted time series (ITS) data: accounting for patient heterogeneity using weighted analysis. 一种改进的中断时间序列(ITS)数据分析方法:使用加权分析考虑患者异质性。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2022-11-01 DOI: 10.1515/ijb-2020-0046

Joycelyne Ewusie, Joseph Beyene, Lehana Thabane, Sharon E Straus, Jemila S Hamid

{"title":"An improved method for analysis of interrupted time series (ITS) data: accounting for patient heterogeneity using weighted analysis.","authors":"Joycelyne Ewusie, Joseph Beyene, Lehana Thabane, Sharon E Straus, Jemila S Hamid","doi":"10.1515/ijb-2020-0046","DOIUrl":"https://doi.org/10.1515/ijb-2020-0046","url":null,"abstract":"Abstract Interrupted time series (ITS) design is commonly used to evaluate the impact of interventions in healthcare settings. Segmented regression (SR) is the most commonly used statistical method and has been shown to be useful in practical applications involving ITS designs. Nevertheless, SR is prone to aggregation bias, which leads to imprecision and loss of power to detect clinically meaningful differences. The objective of this article is to present a weighted SR method, where variability across patients within the healthcare facility and across time points is incorporated through weights. We present the methodological framework, provide optimal weights associated with data at each time point and discuss relevant statistical inference. We conduct extensive simulations to evaluate performance of our method and provide comparative analysis with the traditional SR using established performance criteria such as bias, mean square error and statistical power. Illustrations using real data is also provided. In most simulation scenarios considered, the weighted SR method produced estimators that are uniformly more precise and relatively less biased compared to the traditional SR. The weighted approach also associated with higher statistical power in the scenarios considered. The performance difference is much larger for data with high variability across patients within healthcare facilities. The weighted method proposed here allows us to account for the heterogeneity in the patient population, leading to increased accuracy and power across all scenarios. We recommend researchers to carefully design their studies and determine their sample size by incorporating heterogeneity in the patient population.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10495219","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

Error rate control for classification rules in multiclass mixture models. 多类混合模型分类规则错误率控制。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2022-11-01 DOI: 10.1515/ijb-2020-0105

Tristan Mary-Huard, Vittorio Perduca, Marie-Laure Martin-Magniette, Gilles Blanchard

{"title":"Error rate control for classification rules in multiclass mixture models.","authors":"Tristan Mary-Huard, Vittorio Perduca, Marie-Laure Martin-Magniette, Gilles Blanchard","doi":"10.1515/ijb-2020-0105","DOIUrl":"https://doi.org/10.1515/ijb-2020-0105","url":null,"abstract":"In the context of finite mixture models one considers the problem of classifying as many observations as possible in the classes of interest while controlling the classification error rate in these same classes. Similar to what is done in the framework of statistical test theory, different type I and type II-like classification error rates can be defined, along with their associated optimal rules, where optimality is defined as minimizing type II error rate while controlling type I error rate at some nominal level. It is first shown that finding an optimal classification rule boils down to searching an optimal region in the observation space where to apply the classical Maximum A Posteriori (MAP) rule. Depending on the misclassification rate to be controlled, the shape of the optimal region is provided, along with a heuristic to compute the optimal classification rule in practice. In particular, a multiclass FDR-like optimal rule is defined and compared to the thresholded MAP rules that is used in most applications. It is shown on both simulated and real datasets that the FDR-like optimal rule may be significantly less conservative than the thresholded MAP rule.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10495222","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: 2

Quantifying the extent of visit irregularity in longitudinal data. 量化纵向数据访问不规律性的程度。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2022-11-01 DOI: 10.1515/ijb-2020-0144

Armend Lokku, Catherine S Birken, Jonathon L Maguire, Eleanor M Pullenayegum

{"title":"Quantifying the extent of visit irregularity in longitudinal data.","authors":"Armend Lokku, Catherine S Birken, Jonathon L Maguire, Eleanor M Pullenayegum","doi":"10.1515/ijb-2020-0144","DOIUrl":"https://doi.org/10.1515/ijb-2020-0144","url":null,"abstract":"The timings of visits in observational longitudinal data may depend on the study outcome, and this can result in bias if ignored. Assessing the extent of visit irregularity is important because it can help determine whether visits can be treated as repeated measures or as irregular data. We propose plotting the mean proportions of individuals with 0 visits per bin against the mean proportions of individuals with >1 visit per bin as bin width is varied and using the area under the curve (AUC) to assess the extent of irregularity. The AUC is a single score which can be used to quantify the extent of irregularity and assess how closely visits resemble repeated measures. Simulation results confirm that the AUC increases with increasing irregularity while being invariant to sample size and the number of scheduled measurement occasions. A demonstration of the AUC was performed on the TARGet Kids! study which enrolls healthy children aged 0-5 years with the aim of investigating the relationship between early life exposures and later health problems. The quality of statistical analyses can be improved by using the AUC as a guide to select the appropriate analytic outcome approach and minimize the potential for biased results.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10495215","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

A robust hazard ratio for general modeling of survival-times. 一般生存时间模型的稳健风险比。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2022-11-01 DOI: 10.1515/ijb-2021-0003

Pablo Martínez-Camblor, Todd A MacKenzie, A James O'Malley

{"title":"A robust hazard ratio for general modeling of survival-times.","authors":"Pablo Martínez-Camblor, Todd A MacKenzie, A James O'Malley","doi":"10.1515/ijb-2021-0003","DOIUrl":"https://doi.org/10.1515/ijb-2021-0003","url":null,"abstract":"Hazard ratios (HR) associated with the well-known proportional hazard Cox regression models are routinely used for measuring the impact of one factor of interest on a time-to-event outcome. However, if the underlying real model does not fit with the theoretical requirements, the interpretation of those HRs is not clear. We propose a new index, gHR, which generalizes the HR beyond the underlying survival model. We consider the case in which the study factor is a binary variable and we are interested in both the unadjusted and adjusted effect of this factor on a time-to-event variable, potentially, observed in a right-censored scenario. We propose non-parametric estimations for unadjusted gHR and semi-parametric regression-induced techniques for the adjusted case. The behavior of those estimators is studied in both large and finite sample situations. Monte Carlo simulations reveal that both estimators provide good approximations of their respective inferential targets. Data from the Health and Lifestyle Study are used for studying the relationship of the tobacco use and the age of death and illustrate the practical application of the proposed technique. gHR is a promising index which can help facilitate better understanding of the association of one study factor on a time-dependent outcome.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10495216","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

Review and comparison of treatment effect estimators using propensity and prognostic scores. 使用倾向和预后评分的治疗效果评估器的回顾和比较。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2022-11-01 DOI: 10.1515/ijb-2021-0005

Myoung-Jae Lee, Sanghyeok Lee

引用次数: 3

Penalized likelihood estimation of the proportional hazards model for survival data with interval censoring. 区间筛选生存数据的比例风险模型的惩罚似然估计。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2022-11-01 DOI: 10.1515/ijb-2020-0104

Jun Ma, Dominique-Laurent Couturier, Stephane Heritier, Ian C Marschner

{"title":"Penalized likelihood estimation of the proportional hazards model for survival data with interval censoring.","authors":"Jun Ma, Dominique-Laurent Couturier, Stephane Heritier, Ian C Marschner","doi":"10.1515/ijb-2020-0104","DOIUrl":"https://doi.org/10.1515/ijb-2020-0104","url":null,"abstract":"This paper considers the problem of semi-parametric proportional hazards model fitting where observed survival times contain event times and also interval, left and right censoring times. Although this is not a new topic, many existing methods suffer from poor computational performance. In this paper, we adopt a more versatile penalized likelihood method to estimate the baseline hazard and the regression coefficients simultaneously. The baseline hazard is approximated using basis functions such as M-splines. A penalty is introduced to regularize the baseline hazard estimate and also to ease dependence of the estimates on the knots of the basis functions. We propose a Newton-MI (multiplicative iterative) algorithm to fit this model. We also present novel asymptotic properties of our estimates, allowing for the possibility that some parameters of the approximate baseline hazard may lie on the parameter space boundary. Comparisons of our method against other similar approaches are made through an intensive simulation study. Results demonstrate that our method is very stable and encounters virtually no numerical issues. A real data application involving melanoma recurrence is presented and an R package 'survivalMPL' implementing the method is available on R CRAN.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10499026","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: 4

"Show me the DAG!" “让我看看DAG!”

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2022-10-28 eCollection Date: 2023-11-01 DOI: 10.1515/ijb-2022-0090

Elizabeth F Krakow

引用次数: 0

Statistical modelling of COVID-19 and drug data via an INAR(1) process with a recent thinning operator and cosine Poisson innovations. 利用最近的细化算子和余弦泊松创新，通过INAR(1)过程对COVID-19和药物数据进行统计建模。

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2022-10-28 eCollection Date: 2023-11-01 DOI: 10.1515/ijb-2022-0053

Zohreh Mohammadi, Hassan S Bakouch, Maryam Sharafi

引用次数: 1

A SIMEX approach for meta-analysis of diagnostic accuracy studies with attention to ROC curves. 关注ROC曲线的诊断准确性研究的SIMEX荟萃分析方法

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2022-10-27 eCollection Date: 2023-11-01 DOI: 10.1515/ijb-2022-0012

Annamaria Guolo, Tania Erika Pesantez Cabrera

{"title":"A SIMEX approach for meta-analysis of diagnostic accuracy studies with attention to ROC curves.","authors":"Annamaria Guolo, Tania Erika Pesantez Cabrera","doi":"10.1515/ijb-2022-0012","DOIUrl":"10.1515/ijb-2022-0012","url":null,"abstract":"Bivariate random-effects models represent an established approach for meta-analysis of accuracy measures of a diagnostic test, which are typically given by sensitivity and specificity. A recent formulation of the classical model describes the test accuracy in terms of study-specific Receiver Operating Characteristics curves. In this way, the resulting summary curve can be thought of as an average of the study-specific Receiver Operating Characteristics curves. Within this framework, the paper shows that the standard likelihood approach for inference is prone to several issues. Small sample size can give rise to unreliable conclusions and convergence problems deeply affect the analysis. The proposed alternative is a simulation-extrapolation method, called SIMEX, developed within the measurement error literature. It suits the meta-analysis framework, as the accuracy measures provided by the studies are estimates rather than true values, and thus are prone to error. The methods are compared in a series of simulation studies, covering different scenarios of interest, including deviations from normality assumptions. SIMEX reveals a satisfactory strategy, providing more accurate inferential results if compared to the likelihood approach, while avoiding convergence failure. The approaches are applied to a meta-analysis of the accuracy of the ultrasound exam for diagnosing abdominal tuberculosis in HIV-positive subjects.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45380561","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