Paul Kabaila, Khageswor Giri
Consider a two-treatment, two-period crossover trial, with responses that are continuous random variables. We find a large-sample frequentist 1-alpha confidence interval for the treatment difference that utilizes the uncertain prior information that there is no differential carryover effect.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
继续探索
Freeman has considered the following two-stage procedure for finding a confidence interval for the treatment difference theta, using data from an AB/BA crossover trial. In the first stage, a preliminary test of the null hypothesis that the differential carryover is zero, is carried out. If this hypothesis is accepted then the confidence interval for theta is constructed assuming that the differential carryover is zero. If, on the other hand, this hypothesis is rejected then this confidence interval is constructed using only data from the first period. Freeman has shown that this confidence int…
Likelihood-based Missing Data Analysis in Crossover Trials
针对交叉试验基因表达数据中的缺失问题，采用基于 Monte Carlo EM 的技术进行参数估计，并开发 MCEM 似然比检验来检验固定效应，通过模拟研究验证了方法的有效性。
Statistical Methods for Crossover Trials: A Review of Classical and Recent Developments
本文综述了交叉设计的统计方法进展，重点介绍 AB-BA 设计及其扩展，涵盖连续、多元和分类响应分析，并指出开放问题。
Cluster randomized crossover trials with very few clusters but multiple periods: which analyses for continuous outcomes should be used?
本研究通过模拟评估多种分析方法在极少簇多时期整群随机交叉试验中的表现，发现准确建模簇-时期相关性比选择固定或随机截距更重要，且稀疏设计结果需谨慎解读。
Surrogate-Assisted Estimation of Exposure-Time Effects in Stepped-Wedge Trials with Administratively Censored Outcomes
本文提出一种替代辅助目标最小损失估计器，用于处理行政删失下的嵌套因果函数，通过替代桥表示避免逆概率加权，展示估计器的渐近线性与双鲁棒性，并通过模拟和真实数据验证其稳定性。
We propose a test-based elastic integrative analysis of the randomized trial and real-world data to estimate treatment effect heterogeneity with a vector of known effect modifiers. When the real-world data are not subject to bias, our approach combines the trial and real-world data for efficient estimation. Utilizing the trial design, we construct a test to decide whether or not to use real-world data. We characterize the asymptotic distribution of the test-based estimator under local alternatives. We provide a data-adaptive procedure to select the test threshold that promises the smallest mea…
Combining Unsupervised Learning and Statistical Inference For Multimodal N-of-1 Trials
针对大型多模态N-of-1试验缺乏自动化分析方法的问题，提出结合自编码器与主成分分析的无监督建模方法，无需专家标注即可检测治疗效应，经模拟与临床数据验证有效。
Likelihood-based Inference for Skewed Responses in a Crossover Trial Setup
本文提出了一种用于交叉试验的统计模型，考虑了偏斜响应的线性混合效应模型，并通过EM算法估计参数，用于基因表达研究数据。
Crossover designs are an extremely useful tool to investigators, whilst group sequential methods have proven highly proficient at improving the efficiency of parallel group trials. Yet, group sequential methods and crossover designs have rarely been paired together. One possible explanation for this could be the absence of a formal proof of how to strongly control the familywise error rate in the case when multiple comparisons will be made. Here, we provide this proof, valid for any number of initial experimental treatments and any number of stages, when results are analysed using a linear mix…
The determination of the sample size required by a crossover trial typically depends on the specification of one or more variance components. Uncertainty about the value of these parameters at the design stage means that there is often a risk a trial may be under- or over-powered. For many study designs, this problem has been addressed by considering adaptive design methodology that allows for the re-estimation of the required sample size during a trial. Here, we propose and compare several approaches for this in multi-treatment crossover trials. Specifically, regulators favour re-estimation p…
Behavioral Carry-Over Effect and Power Consideration in Crossover Trials
本文在潜在结果框架下分析行为残留效应对交叉试验估计与检验效能的影响，推导其优于平行组设计的条件，并提出协变量调整方法。
Efficient designs for multivariate crossover trials
本文研究多变元交叉试验的高效设计，提出多变元固定效应模型，在比例或广义马尔可夫协方差下利用信息矩阵确定高效设计，并验证了正交阵列设计效率。
Utilizing subgroup information in random-effects meta-analysis of few studies
针对少量研究的随机效应meta分析，该文提出基于亚组数据的推断方法，推导两种异质性估计量，采用t分位数区间并结合灵活自由度，经模拟验证性能良好且给出亚组选择建议。
Studying Optimal Designs for Multivariate Crossover Trials
本文针对多变量交叉试验，在响应间不相关而响应内相关及异方差误差假设下，研究直接效应信息矩阵，并证明当周期数等于处理数且不小于3时，类型I强度2的正交阵列设计具有A-、D-和E-最优性。
Augmented two-stage estimation for treatment crossover in oncology trials: Leveraging external data for improved precision
针对肿瘤RCT中治疗交叉导致长期效果估计不精确的问题，提出ATSE方法结合RCT未交叉数据与外部数据形成混合组，模拟显示其在无混杂外部数据时比TSE和外部对照组方法偏差更小、精度更高，混杂时偏差程度也更低。
A Unified Three-State Model Framework for Analysis of Treatment Crossover in Survival Trials
针对生存试验中的治疗交叉问题，本文提出统一三状态模型（TSM）框架，梳理现有方法的假设、偏倚与局限，并给出新插补方法和模拟验证。
A Bayesian approach to the survivor average causal effect in cluster-randomized crossover trials
本文提出了一种贝叶斯方法，用于估计CRXO试验中因死亡导致的截断问题，通过主效应分层确定幸存者平均因果效应。
This article discusses D-optimal Bayesian crossover designs for generalized linear models. Crossover trials with t treatments and p periods, for $t <= p$, are considered. The designs proposed in this paper minimize the log determinant of the variance of the estimated treatment effects over all possible allocation of the n subjects to the treatment sequences. It is assumed that the p observations from each subject are mutually correlated while the observations from different subjects are uncorrelated. Since main interest is in estimating the treatment effects, the subject effect is assumed to b…
Recently there has been much work on early phase cancer designs that incorporate both toxicity and efficacy data, called Phase I-II designs because they combine elements of both phases. However, they do not explicitly address the Phase II hypothesis test of $H_0: p\le p_0$, where $p$ is the probability of efficacy at the estimated maximum tolerated dose (MTD) $\widehatη$ from Phase I and $p_0$ is the baseline efficacy rate. Standard practice for Phase II remains to treat $p$ as a fixed, unknown parameter and to use Simon's 2-stage design with all patients dosed at $\widehatη$. We propose a Pha…
What is estimated in cluster randomized crossover trials with informative sizes? -- A survey of estimands and common estimators
该研究针对存在信息性规模的2周期整群随机交叉试验，明确了四类加权/未加权估计方法对不同层面治疗效应估计量的一致性，通过模拟与实例验证了嵌套可交换混合效应模型的偏倚风险及其他方法的适用场景。
An Online Meta-Level Adaptive Design Framework with Targeted Learning Inference: Applications to Evaluating and Utilizing Surrogate Outcomes in Adaptive Designs
本文提出一种在线元级自适应设计框架，用于实时评估和选择候选自适应设计，通过定义新的因果估计量和目标最大似然估计器，量化替代性结局的效用，以加速检测异质治疗效应并改善参与者结果。
Statistical modeling to adjust for time trends in adaptive platform trials utilizing non-concurrent controls
针对自适应平台试验中利用非同期对照可能因时间趋势引入偏倚的问题，提出两种扩展模型（固定长度日历区间和替代时间调整，含随机效应与样条），模拟与案例显示样条可控制I类错误并提升效能，但时期调整固定效应模型对任意趋势最稳健。
Doubly protected estimation for survival outcomes utilizing external controls for randomized clinical trials
针对随机试验对照组小且外部对照存在异质性偏倚的问题，提出基于双重稳健估计与 DR-Learner 选择性借用的限制性平均生存时间差估计框架，并通过模拟和 Galcanezumab 偏头痛数据验证其有效性。
Conventional methods for analyzing composite endpoints in clinical trials often only focus on the time to the first occurrence of all events in the composite. Therefore, they have inherent limitations because the individual patients' first event can be the outcome of lesser clinical importance. To overcome this limitation, the concept of the win ratio (WR), which accounts for the relative priorities of the components and gives appropriate priority to the more clinically important event, was examined. For example, because mortality has a higher priority than hospitalization, it is reasonable to…
In a randomized controlled trial, treatment switching (also called contamination or crossover) occurs when a patient initially assigned to one treatment arm changes to another arm during the course of follow-up. Overlooking treatment switching might substantially bias the evaluation of treatment efficacy or safety. To account for treatment switching, instrumental variable (IV) methods by leveraging the initial randomized assignment as an IV serve as natural adjustment methods because they allow dependent treatment switching possibly due to underlying prognoses. However, the ``exclusion restric…
The field of precision medicine aims to tailor treatment based on patient-specific factors in a reproducible way. To this end, estimating an optimal individualized treatment regime (ITR) that recommends treatment decisions based on patient characteristics to maximize the mean of a pre-specified outcome is of particular interest. Several methods have been proposed for estimating an optimal ITR from clinical trial data in the parallel group setting where each subject is randomized to a single intervention. However, little work has been done in the area of estimating the optimal ITR from crossove…
NCC: An R-package for analysis and simulation of platform trials with non-concurrent controls
本研究推出R包NCC，用于含非同期对照的平台试验的设计与分析，支持多场景下的试验模拟与分析方法性能评估，还通过示例展示了包的使用方式。
Sample size calculations for multilevel factorial longitudinal cluster randomised trials
本文提出针对多级干预的纵向集群随机试验样本量计算方法，适用于连续型结局，支持评估个体与集群干预及交互作用。
Causal inference for N-of-1 trials
本文提出了一种基于因果推断框架的N-of-1试验分析方法，定义了U-CATE并探讨了不同因果模型下的估计策略。
Suppose one wishes to estimate the effect of a binary treatment on a binary endpoint conditional on a post-randomization quantity in a counterfactual world in which all subjects received treatment. It is generally difficult to identify this parameter without strong, untestable assumptions. It has been shown that identifiability assumptions become much weaker under a crossover design in which subjects not receiving treatment are later given treatment. Under the assumption that the post-treatment biomarker observed in these crossover subjects is the same as would have been observed had they rece…
Optimal Sample Size Calculation in Cost-Effectiveness Longitudinal Cluster Randomized Trials
本文提出一种用于纵向集群随机试验的成本效益分析设计框架，针对平行臂、交叉和阶梯楔形三种设计变体，推导方差表达式并提出标准化天花板比，以优化样本量计算。
Improving precision of cumulative incidence estimates in randomized controlled trials with external controls
本研究提出三稳健估计器，利用外部对照提升随机对照试验中累积发生率估计精度，通过时间特定权重实现可比性，模拟和心血管试验数据验证了精度增益。
How to achieve model-robust inference in stepped wedge trials with model-based methods?
本研究针对阶梯楔形试验中基于模型的分析方法在模型误设下的性质未被系统探究的问题，证明了边际治疗效应估计一致性的条件，提出结合三明治方差估计与g-computation实现模型稳健推断，并通过模拟和实例验证了结论。
A Bayesian likely responder approach for the analysis of randomized controlled trials
本文提出一种贝叶斯两阶段方法，用于随机对照试验中亚群体识别与治疗效应推断，通过整合模型不确定性提升置信区间校准性，并在新冠治疗试验中验证了亚群体治疗效应的显著差异。
Historical data about disease outcomes can be integrated into the analysis of clinical trials in many ways. We build on existing literature that uses prognostic scores from a predictive model to increase the efficiency of treatment effect estimates via covariate adjustment. Here we go further, utilizing a Bayesian framework that combines prognostic covariate adjustment with an empirical prior distribution learned from the predictive performances of the prognostic model on past trials. The Bayesian approach interpolates between prognostic covariate adjustment with strict type I error control wh…
In this paper, we propose a data-adaptive empirical likelihood-based approach for treatment effect estimation and inference, which overcomes the obstacle of the traditional empirical likelihood-based approaches in the high-dimensional setting by adopting penalized regression and machine learning methods to model the covariate-outcome relationship. In particular, we show that our procedure successfully recovers the true variance of Zhang's treatment effect estimator (Zhang, 2018) by utilizing a data-splitting technique. Our proposed estimator is proved to be asymptotically normal and semiparame…
Fixed-Effects Models for Causal Inference in Longitudinal Cluster Randomized and Quasi-Experimental Trials
本文探讨了固定效应模型在纵向集群试验中的稳健性，证明其可通过M估计框架有效估计超总体边际估计量，并通过模拟和案例研究展示了其作为混合效应模型的稳健替代方案。
Cookstove replacement trials have found mixed results on their impact on respiratory health. The limited range of concentrations and small sample sizes of individual studies are important factors that may be limiting their statistical power. We present a hierarchical approach to modeling exposure concentrations and pooling data from multiple studies in order to estimate a common exposure-response curve. The exposure concentration model accommodates temporally sparse, clustered longitudinal observations. The exposure-response curve model provides a flexible, semi-parametric estimate of the expo…
Inference of treatment effect and its regional modifiers using restricted mean survival time in multi-regional clinical trials
针对多区域临床试验中区域特征差异易致治疗效应估计偏差、事件时间结局研究多依赖风险比的问题，提出结合抽样逆概率与校准加权的限制性平均生存时间估计推断方法，兼具理论支撑与实际有效性。
Biomarker measurements can be relatively easy and quick to obtain and they are useful to investigate whether a compound works as intended on a mechanistic, pharmacological level. In some situations, it is realistic to assume that patients, whose post-baseline biomarker levels indicate that they do not sufficiently respond to the drug, are also unlikely to respond on clinically relevant long term outcomes (such as time-to-event). However the determination of the treatment effect in the subgroup of patients that sufficiently respond to the drug according to their biomarker levels is not straight…
Publication bias is a major concern in conducting systematic reviews and meta-analyses. Various sensitivity analysis or bias-correction methods have been developed based on selection models and they have some advantages over the widely used bias-correction method of the trim-and-fill method. However, likelihood methods based on selection models may have difficulty in obtaining precise estimates and reasonable confidence intervals or require a complicated sensitivity analysis process. In this paper, we develop a simple publication bias adjustment method utilizing information on conducted but st…
Instrumental Variable Approach to Estimating Individual Causal Effects in N-of-1 Trials: Application to ISTOP Study
本研究针对 N-of-1 试验提出一种贝叶斯工具变量方法，通过潜在结构模型建模混杂机制以解决不完全依从、二元变量不可折叠性及序列推断问题，有效降低偏差并提高个体因果效应估计的覆盖率，并应用于 I-STOP-AFib 研究评估酒精对心房颤动的影响。
A Framework for Parametric Time-Varying Treatment Effects in Multiple Intervention Stepped Wedge Design Clinical Trials in the Presence of Non-Uniform Cluster-Period Correlation Structures
研究多干预阶梯楔形设计临床试验中参数时变治疗效果，开发统一框架将参数暴露-反应函数纳入设计矩阵，推导相关GLS表达式，揭示时变效应影响，表明估计量依赖假设，不考虑会致功效校准错误和推断偏差。
A comparison of methods for estimating the average treatment effect on the treated for externally controlled trials
本研究通过模拟比较了多种估计外部对照单臂试验中ATT的方法，发现双重稳健方法偏倚更小，非匹配方法标准差更小，且可识别性假设对方法性能至关重要。
A tutorial on conducting sample size and power calculations for detecting treatment effect heterogeneity in cluster randomized trials with linear mixed models
本文探讨了在集群随机试验中使用线性混合模型检测治疗效应异质性的样本量和功效计算方法，提供了计算工具和关键考虑因素。
Use of historical control data to augment a small internal control arm in a randomized control trial (RCT) can lead to significant improvement of the efficiency of the trial. It introduces the risk of potential bias, since the historical control population is often rather different from the RCT. Power prior approaches have been introduced to discount the historical data to mitigate the impact of the population difference. However, even with a Bayesian dynamic borrowing which can discount the historical data based on the outcome similarity of the two populations, a considerable population diffe…
扫码添加微信好友，提出您的宝贵建议 👇
💡 备注请填写：网站反馈
发表机构由 AI 从论文文本抽取，如发现错误，欢迎反馈修正建议。