Abstract:
:Covariate-adaptive designs are widely used to balance covariates and maintain randomization in clinical trials. Adaptive designs for discrete covariates and their asymptotic properties have been well studied in the literature. However, important continuous covariates are often involved in clinical studies. Simply discretizing or categorizing continuous covariates can result in loss of information. The current understanding of adaptive designs with continuous covariates lacks a theoretical foundation as the existing works are entirely based on simulations. Consequently, conventional hypothesis testing in clinical trials using continuous covariates is still not well understood. In this paper, we establish a theoretical framework for hypothesis testing on adaptive designs with continuous covariates based on linear models. For testing treatment effects and significance of covariates, we obtain the asymptotic distributions of the test statistic under null and alternative hypotheses. Simulation studies are conducted under a class of covariate-adaptive designs, including the p-value-based method, the Su's percentile method, the empirical cumulative-distribution method, the Kullback-Leibler divergence method, and the kernel-density method. Key findings about adaptive designs with independent covariates based on linear models are (1) hypothesis testing that compares treatment effects are conservative in terms of smaller type I error, (2) hypothesis testing using adaptive designs outperforms complete randomization method in terms of power, and (3) testing on significance of covariates is still valid.
journal_name
Stat Methods Med Resjournal_title
Statistical methods in medical researchauthors
Li X,Zhou J,Hu Fdoi
10.1177/0962280218770231subject
Has Abstractpub_date
2019-06-01 00:00:00pages
1609-1621issue
6eissn
0962-2802issn
1477-0334journal_volume
28pub_type
杂志文章abstract::To project national hepatitis C virus (HCV) burden, unbiased estimation of HCV progression to liver cirrhosis is required for the whole community of HCV-infected individuals. However, widely varying estimates of progression rates to cirrhosis have been produced. This disparity is partly associated with the statistical...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280208094688
更新日期:2009-06-01 00:00:00
abstract::Purpose The prevalence estimates of binary variables in sample surveys are often subject to two systematic errors: measurement error and nonresponse bias. A multiple-bias analysis is essential to adjust for both biases. Methods In this paper, we linked the latent class log-linear and proxy pattern-mixture models to ad...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217690939
更新日期:2018-10-01 00:00:00
abstract::Competing risks data often exist within a center in multi-center randomized clinical trials where the treatment effects or baseline risks may vary among centers. In this paper, we propose a subdistribution hazard regression model with multivariate frailty to investigate heterogeneity in treatment effects among centers...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214526193
更新日期:2016-12-01 00:00:00
abstract::Health data may be collected across one spatial framework (e.g. health provider agencies), but contrasts in health over another spatial framework (neighbourhoods) may be of policy interest. In the UK, population prevalence totals for chronic diseases are provided for populations served by general practitioner practice...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280212447150
更新日期:2014-04-01 00:00:00
abstract::This review provides an overview of forensic inference from genetic markers. Because the judge and jurors are charged with decision-making, the forensic expert's job is to provide a useful summary of the evidence to the court. Hence, this review focuses on the likelihood ratio as a means of summarizing the genetic dat...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/096228029300200304
更新日期:1993-01-01 00:00:00
abstract::Increasing the clinical applicability of functional neuroimaging technology is an emerging objective, e.g. for diagnostic and treatment purposes. We propose a novel Bayesian spatial hierarchical framework for predicting follow-up neural activity based on an individual's baseline functional neuroimaging data. Our appro...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280212448972
更新日期:2013-08-01 00:00:00
abstract::Studies of HIV dynamics in AIDS research are very important for understanding pathogenesis of HIV infection and for assessing the potency of antiviral therapies. Since the viral dynamic results from clinical data were first published by Ho et al. and Wei et al., the study of HIV-1 dynamics in vivo has drawn a great at...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1191/0962280205sm390oa
更新日期:2005-04-01 00:00:00
abstract::The analysis of health care costs is complicated by the skewed and heteroscedastic nature of their distribution with possibly additional zero values. Statistical methods that do not adjust for these features can lead to incorrect conclusions. This paper reviews recent developments in statistical methods for the analys...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1191/0962280202sm290ra
更新日期:2002-08-01 00:00:00
abstract::Many longitudinal studies observe time to occurrence of a clinical event such as death, while also collecting serial measurements of one or more biomarkers that are predictive of the event, or are surrogate outcomes of interest. Joint modeling can be used to examine the relationship between the biomarker and the event...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218764193
更新日期:2019-05-01 00:00:00
abstract::Surveys are key means of obtaining policy-relevant information not available from routine sources. Bias arising from non-participation is typically handled by applying weights derived from limited socio-demographic characteristics. This approach neither captures nor adjusts for differences in health and related behavi...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219854482
更新日期:2020-04-01 00:00:00
abstract::Clustered data is not simply correlated data, but has its own unique aspects. In this paper, various methods for correlated receiver operating characteristic (ROC) curve data that have been extended specifically to clustered data are reviewed. For those methods that have not yet been extended, suggestions for their ap...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/096228029800700402
更新日期:1998-12-01 00:00:00
abstract::We propose a novel likelihood method for analyzing time-to-event data when multiple events and multiple missing data intervals are possible prior to the first observed event for a given subject. This research is motivated by data obtained from a heart monitor used to track the recovery process of subjects experiencing...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280212466089
更新日期:2016-04-01 00:00:00
abstract::In many experiments and especially in translational and preclinical research, sample sizes are (very) small. In addition, data designs are often high dimensional, i.e. more dependent than independent replications of the trial are observed. The present paper discusses the applicability of max t-test-type statistics (mu...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280220970228
更新日期:2020-11-24 00:00:00
abstract::Several epidemiological parameters have been introduced for quantifying the population impact of a certain exposure on morbidity on a population level, termed 'attributable risk' (AR). Of these definitions, the AR as suggested by Levin in 1953 or some algebraic transformations of it are most commonly used. A structure...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/096228020101000305
更新日期:2001-06-01 00:00:00
abstract::Exposure measurement error in epidemiological studies is recognized as a feature that must be considered because of the potential bias that can result in estimates of the exposure-disease association. Most of the work to date has focused on methods of analysis that adjust for the resultant bias, but the implications o...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/096228029500400405
更新日期:1995-12-01 00:00:00
abstract::This paper reviews models for incomplete continuous and categorical longitudinal data. In terms of Rubin's classification of missing value processes we are specifically concerned with the problem of nonrandom missingness. A distinction is drawn between the classes of selection and pattern-mixture models and, using sev...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/096228029900800105
更新日期:1999-03-01 00:00:00
abstract::With the emergence of rich information on biomarkers after treatments, new types of prognostic tools are being developed: dynamic prognostic tools that can be updated at each new biomarker measurement. Such predictions are of interest in oncology where after an initial treatment, patients are monitored with repeated b...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214535763
更新日期:2016-12-01 00:00:00
abstract::In this article, we present an overview and tutorial of statistical methods for meta-analysis of diagnostic tests under two scenarios: (1) when the reference test can be considered a gold standard and (2) when the reference test cannot be considered a gold standard. In the first scenario, we first review the conventio...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/0962280213492588
更新日期:2016-08-01 00:00:00
abstract::Sample size calculations are needed to design and assess the feasibility of case-control studies. Although such calculations are readily available for simple case-control designs and univariate analyses, there is limited theory and software for multivariate unconditional logistic analysis of case-control data. Here we...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217737157
更新日期:2019-03-01 00:00:00
abstract::Trials run in either rare diseases, such as rare cancers, or rare sub-populations of common diseases are challenging in terms of identifying, recruiting and treating sufficient patients in a sensible period. Treatments for rare diseases are often designed for other disease areas and then later proposed as possible tre...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280216662070
更新日期:2018-05-01 00:00:00
abstract::In multi-regional trials, the underlying overall and region-specific accrual rates often do not hold constant over time and different regions could have different start-up times, which combined with initial jump in accrual within each region often leads to a discontinuous overall accrual rate, and these issues associa...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214557581
更新日期:2017-04-01 00:00:00
abstract::This article discusses and extends statistical models to jointly analyse the spatial variation of rates of several diseases with common risk factors. We start with a review of methods for separate analyses of diseases, then move to ecological regression approaches, where the rates from one of the diseases enter as sur...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1191/0962280205sm389oa
更新日期:2005-02-01 00:00:00
abstract::Clinical trials investigating the efficacy of two or more doses of an experimental treatment compared to a single reference arm are not uncommon. In such situations, if each dose is compared to the reference arm using an un-adjusted significance level, consideration of the Type I familywise error is likely to be requi...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280210378943
更新日期:2011-12-01 00:00:00
abstract::Improving the quality of care that patients receive is a major focus of clinical research, particularly in the setting of cardiovascular hospitalization. Quality improvement studies seek to estimate and visualize the degree of variability in dichotomous treatment patterns and outcomes across different providers, where...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217754230
更新日期:2019-04-01 00:00:00
abstract::The positivity assumption, or the experimental treatment assignment (ETA) assumption, is important for identifiability in causal inference. Even if the positivity assumption holds, practical violations of this assumption may jeopardize the finite sample performance of the causal estimator. One of the consequences of p...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218774817
更新日期:2019-06-01 00:00:00
abstract::In this paper, we develop a simple diagnostic test for the random-effects distribution in mixed models. The test is based on the gradient function, a graphical tool proposed by Verbeke and Molenberghs to check the impact of assumptions about the random-effects distribution in mixed models on inferences. Inference is c...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214564721
更新日期:2017-04-01 00:00:00
abstract::In many applications of zero-inflated models, score tests are often used to evaluate whether the population heterogeneity as implied by these models is consistent with the data. The most frequently cited justification for using score tests is that they only require estimation under the null hypothesis. Because this es...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280220937324
更新日期:2020-12-01 00:00:00
abstract::Identification of cancer patient subgroups using high throughput genomic data is of critical importance to clinicians and scientists because it can offer opportunities for more personalized treatment and overlapping treatments of cancers. In spite of tremendous efforts, this problem still remains challenging because o...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217752980
更新日期:2019-07-01 00:00:00
abstract::It is a common practice to analyze longitudinal data frequently arisen in medical studies using various mixed-effects models in the literature. However, the following issues may standout in longitudinal data analysis: (i) In clinical practice, the profile of each subject's response from a longitudinal study may follow...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214544207
更新日期:2017-02-01 00:00:00
abstract::Most statistical developments in the joint modelling area have focused on the shared random-effect models that include characteristics of the longitudinal marker as predictors in the model for the time-to-event. A less well-known approach is the joint latent class model which consists in assuming that a latent class s...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/0962280212445839
更新日期:2014-02-01 00:00:00