Abstract:
:Bayes or empirical Bayes methods to improve inferential accuracy for a population mean has been widely adopted in medical research. As the joint prior distribution of both the mean and variance parameters can be difficult to specify or estimate, most of these methods have relied on certain level of simplifications of the joint prior, which could lead to difficulty in the interpretation of the posterior distribution or compromised inferential accuracy. We propose a framework of interval estimation using existing knowledge or data on the effect size to address this difficulty. Our method has two unique characteristics. First, the interpretation of the interval bears the spirit of both Frequentist and Bayesian thinking. For this reason, it will be called FB interval. Second, we define a new quantity, the hybrid effect size, which is a key quantity that mediates the construction of the FB interval when the population variance is unknown. A simulation study and a real data example are presented to evaluate and illustrate our method.
journal_name
Stat Methods Med Resjournal_title
Statistical methods in medical researchauthors
Shen Cdoi
10.1177/0962280218773537subject
Has Abstractpub_date
2019-06-01 00:00:00pages
1703-1715issue
6eissn
0962-2802issn
1477-0334journal_volume
28pub_type
杂志文章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 disc...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218770231
更新日期:2019-06-01 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::Comparison of sequences that have descended from a common ancestor based on an explicit stochastic model of substitutions, insertions and deletions has risen to prominence in the last decade. Making statements about the positions of insertions-deletions (abbr. indels) is central in sequence and genome analysis and is ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280208099500
更新日期:2009-10-01 00:00:00
abstract::Cancer patients are subject to multiple competing risks of death and may die from causes other than the cancer diagnosed. The probability of not dying from the cancer diagnosed, which is one of the patients' main concerns, is sometimes called the 'personal cure' rate. Two approaches of modelling competing-risk surviva...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280209347046
更新日期:2011-06-01 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::Statistical models of breast cancer tumour progression have been used to further our knowledge of the natural history of breast cancer, to evaluate mammography screening in terms of mortality, to estimate overdiagnosis, and to estimate the impact of lead-time bias when comparing survival times between screen detected ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217734583
更新日期:2019-03-01 00:00:00
abstract::A bivariate generalised linear mixed model is often used for meta-analysis of test accuracy studies. The model is complex and requires five parameters to be estimated. As there is no closed form for the likelihood function for the model, maximum likelihood estimates for the parameters have to be obtained numerically. ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219853602
更新日期:2020-04-01 00:00:00
abstract::In the field of diagnostic studies for tree or umbrella ordering, under which the marker measurement for one class is lower or higher than those for the rest unordered classes, there exist a few diagnostic measures such as the naive AUC ( NAUC), the umbrella volume ( UV), and the recently proposed TAUC, i.e. area unde...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218755810
更新日期:2019-05-01 00:00:00
abstract::Tracking a subject's risk factors or health status over time is an important objective in long-term epidemiological studies with repeated measurements. An important issue of time-trend tracking is to define appropriate statistical indices to quantitatively measure the tracking abilities of the targeted risk factors or...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219839427
更新日期:2020-02-01 00:00:00
abstract::We propose a semiparametric multi-state frailty model to analyze clustered event-history data subject to interval censoring. The proposed model is motivated by an attempt to study the life course of dental caries at the tooth level, taking into account the multiplicity of caries states and the intra-oral clustering of...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218788383
更新日期:2019-09-01 00:00:00
abstract::In medical sciences, we often encounter longitudinal temporal relationships that are non-linear in nature. The influence of risk factors may also change across longitudinal follow-up. A system of multiphase non-linear mixed effects model is presented to model temporal patterns of longitudinal continuous measurements, ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214537255
更新日期:2017-02-01 00:00:00
abstract::Stochastic transmission dynamic models are needed to quantify the uncertainty in estimates and predictions during outbreaks of infectious diseases. We previously developed a calibration method for stochastic epidemic compartmental models, called Multiple Shooting for Stochastic Systems (MSS), and demonstrated its comp...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218805780
更新日期:2019-12-01 00:00:00
abstract::One of the main advantages of Bayesian analyses of clinical trials is their ability to formally incorporate skepticism about large treatment effects through the use of informative priors. We conducted a simulation study to assess the performance of informative normal, Student- t, and beta distributions in estimating r...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280215620828
更新日期:2018-01-01 00:00:00
abstract::A growing body of evidence suggests that genetic factors have an important influence on the onset and course of smoking. Here we review some of the statistical methods that have been used to test for genetic influences on smoking behaviour, with a particular focus on studies of large national twin samples. We show how...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/096228029800700205
更新日期:1998-06-01 00:00:00
abstract::In biomedical research, various longitudinal markers measuring different quantities are often collected over time. For example, repeated measures of psychometric scores are very informative about the degradation process toward dementia. These trajectories are generally nonlinear with an acceleration of the decline a f...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219898719
更新日期:2020-09-01 00:00:00
abstract::In many longitudinal studies, evaluating the effect of a binary or continuous predictor variable on the rate of change of the outcome, i.e. slope, is often of primary interest. Sample size determination of these studies, however, is complicated by the expectation that missing data will occur due to missed visits, earl...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280212437452
更新日期:2015-12-01 00:00:00
abstract::Regression models are frequently used to model the functional relationship between an interesting outcome parameter and one or more potentially relevant explanatory variables. Objectives can be to set up as a prognostic model, for example, or an estimation model for a certain parameter of interest. Determining half-li...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280213502403
更新日期:2016-10-01 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::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::Mixed models estimated by maximum likelihood and marginal models estimated by generalized estimating equations are the standard methods for the analysis of longitudinal data. However, their use is highly debated when attrition may be due to death. While some authors consider that mixed model estimates are interpretabl...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217723675
更新日期:2019-02-01 00:00:00
abstract::Count responses are becoming increasingly important in biostatistical analysis because of the development of new biomedical techniques such as next-generation sequencing and digital polymerase chain reaction; a commonly met problem in modeling them with the popular Poisson model is overdispersion. Although it has been...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280215583397
更新日期:2017-06-01 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::Variable selection in semiparametric mixed models for longitudinal data remains a challenge, especially in the presence of multiple correlated outcomes. In this paper, we propose a model selection procedure that simultaneously selects fixed and random effects using a maximum penalized likelihood method with the adapti...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217690769
更新日期:2018-10-01 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::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::In the clinical development of some new infectious disease drugs, early clinical pharmacology trials may predict with high confidence that the efficacious doses are well below the range of the safety margin. In this case, a dose-ranging study may be unnecessary after a proof-of-concept (PoC) study testing the highest ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218807950
更新日期:2019-12-01 00:00:00
abstract::The mixed effects model for repeated measures has been widely used for the analysis of longitudinal clinical data collected at a number of fixed time points. We propose a robust extension of the mixed effects model for repeated measures for skewed and heavy-tailed data on basis of the multivariate skew-t distribution,...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219865579
更新日期:2020-06-01 00:00:00
abstract::In this paper age-space-time models based on one and two-dimensional P-splines with B-spline bases are proposed for smoothing mortality rates, where both fixed relative scale and scale invariant two-dimensional penalties are examined. Model fitting and inference are carried out using integrated nested Laplace approxim...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217726802
更新日期:2019-02-01 00:00:00
abstract::For semi-continuous data which are a mixture of true zeros and continuously distributed positive values, the use of two-part mixed models provides a convenient modelling framework. However, deriving population-averaged (marginal) effects from such models is not always straightforward. Su et al. presented a model that ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280213509798
更新日期:2016-10-01 00:00:00
abstract::Pediatric cardiac surgery may lead to poor outcomes such as acute kidney injury (AKI) and prolonged hospital length of stay (LOS). Plasma and urine biomarkers may help with early identification and prediction of these adverse clinical outcomes. In a recent multi-center study, 311 children undergoing cardiac surgery we...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214530608
更新日期:2016-12-01 00:00:00