Abstract:
:Data in many experiments arise as curves and therefore it is natural to use a curve as a basic unit in the analysis, which is termed functional data analysis (FDA). In longitudinal studies, recent developments in FDA have extended classical linear models and linear mixed effects models to functional linear models (also termed varying-coefficient models) and functional mixed effects models. In this paper we focus our review on the functional mixed effects models using smoothing splines, because functional linear models are special cases of this more general framework. Due to the connection between smoothing splines and linear mixed effects models, functional mixed effects models can be fitted using existing software such as SAS Proc Mixed. A case study is presented as an illustration.
journal_name
Stat Methods Med Resjournal_title
Statistical methods in medical researchauthors
Guo Wdoi
10.1191/0962280204sm352rasubject
Has Abstractpub_date
2004-02-01 00:00:00pages
49-62issue
1eissn
0962-2802issn
1477-0334journal_volume
13pub_type
杂志文章,评审abstract::To evaluate the antiretroviral activity of antiretroviral agents and to compare the effects of two different antiretroviral agents, we propose a non-parametric mixed-effects model to investigate change of CD4+ counts. The proposed model and methods are applied to analyse the data from PACTG345 study. Population and in...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280206075524
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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
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abstract::Sample selection arises when the outcome of interest is partially observed in a study. Although sophisticated statistical methods in the parametric and non-parametric framework have been proposed to solve this problem, it is yet unclear how to deal with selectively missing covariate data using simple multiple imputati...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217715663
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abstract::The semiparametric Cox regression model is often fitted in the modeling of survival data. One of its main advantages is the ease of interpretation, as long as the hazards rates for two individuals do not vary over time. In practice the proportionality assumption of the hazards may not be true in some situations. In ad...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219883905
更新日期:2020-08-01 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
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abstract::This paper illustrates the use of multidimensional scaling methods (MDS) to examine space-time patterns in epidemic data. The paper begins by outlining the principles of MDS. The model is then formally specified and illustrated by application to two data sets. The first is partly a tutorial example. It uses monthly re...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/096228029500400202
更新日期:1995-06-01 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::Cluster randomized and multicentre trials evaluate the effect of a treatment on persons nested within clusters, for instance patients within clinics or pupils within schools. Although equal sample sizes per cluster are generally optimal for parameter estimation, they are rarely feasible. This paper addresses the relat...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280206079018
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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 ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218773537
更新日期:2019-06-01 00:00:00
abstract::Excessive zeros are common in practice and may cause overdispersion and invalidate inference when fitting Poisson regression models. There is a large body of literature on zero-inflated Poisson models. However, methods for testing whether there are excessive zeros are less well developed. The Vuong test comparing a Po...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217749991
更新日期:2019-04-01 00:00:00
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journal_title:Statistical methods in medical research
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doi:10.1177/0962280217704451
更新日期:2018-12-01 00:00:00
abstract::Publication bias frequently appears in meta-analyses when the included studies' results (e.g., p-values) influence the studies' publication processes. Some unfavorable studies may be suppressed from publication, so the meta-analytic results may be biased toward an artificially favorable direction. Many statistical tes...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280220910172
更新日期:2020-10-01 00:00:00
abstract:BACKGROUND:When trials are subject to departures from randomised treatment, simple statistical methods that aim to estimate treatment efficacy, such as per protocol or as treated analyses, typically introduce selection bias. More appropriate methods to adjust for departure from randomised treatment are rarely employed,...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217735560
更新日期:2019-03-01 00:00:00
abstract::Measurement error is a serious problem in the analysis of epidemiological data. In the past 20 years, a large number of methods for the correction of measurement error have been developed. While at the beginning mostly methods for cohort studies were considered, recently more attention has been paid to case-control st...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/096228020000900504
更新日期:2000-10-01 00:00:00
abstract::Dependent binary response data arise frequently in practice due to repeated measurements in longitudinal studies or to subsampling primary sampling units as in fields such as teratology and ophthalmology. Several classes of approaches have recently been proposed to analyse such repeated binary outcome data. The differ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/096228029200100303
更新日期:1992-01-01 00:00:00
abstract::Post-therapeutic surveillance is one important component of cancer care. However, there still is no evidence-based strategies to schedule patients' follow-up examinations. Our approach is based on the modeling of the probability of the onset of relapse at an early asymptotic or preclinical stage and its transition to ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214524178
更新日期:2016-12-01 00:00:00
abstract::Spatial resolution plays an important role in functional magnetic resonance imaging studies as the signal-to-noise ratio increases linearly with voxel volume. In scientific studies, where functional magnetic resonance imaging is widely used, the standard spatial resolution typically used is relatively low which ensure...
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doi:10.1177/0962280217752378
更新日期:2019-04-01 00:00:00
abstract::Binary logistic regression is one of the most frequently applied statistical approaches for developing clinical prediction models. Developers of such models often rely on an Events Per Variable criterion (EPV), notably EPV ≥10, to determine the minimal sample size required and the maximum number of candidate predictor...
journal_title:Statistical methods in medical research
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doi:10.1177/0962280218784726
更新日期:2019-08-01 00:00:00
abstract::The random effects model in meta-analysis is a standard statistical tool often used to analyze the effect sizes of the quantity of interest if there is heterogeneity between studies. In the special case considered here, meta-analytic data contain only the sample means in two treatment arms and the sample sizes, but no...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217718867
更新日期:2019-01-01 00:00:00
abstract::Joint models for recurrent and terminal events have not been yet developed for clustered data. The goals of our study are to develop a statistical framework for modelling clustered recurrent and terminal events and to perform dynamic predictions of the terminal event in family studies. We propose a joint nested frailt...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219863076
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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
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abstract::Colorectal cancer is the second leading cause of death from cancer in the United States. To facilitate the efficiency of colorectal cancer screening, there is a need to stratify risk for colorectal cancer among the 90% of US residents who are considered "average risk." In this article, we investigate such risk stratif...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280213497432
更新日期:2016-08-01 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
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doi:10.1177/0962280214544207
更新日期:2017-02-01 00:00:00
abstract::In many health studies, researchers are interested in estimating the treatment effects on the outcome around and through an intermediate variable. Such causal mediation analyses aim to understand the mechanisms that explain the treatment effect. Although multiple mediators are often involved in real studies, most of t...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280215615899
更新日期:2018-01-01 00:00:00
abstract::DNA methylation has been shown to play an important role in many complex diseases. The rapid development of high-throughput DNA methylation scan technologies provides great opportunities for genomewide DNA methylation-disease association studies. As methylation is a dynamic process involving time, it is quite plausibl...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280216683571
更新日期:2018-09-01 00:00:00
abstract::Common limitations of clustering methods include the slow algorithm convergence, the instability of the pre-specification on a number of intrinsic parameters, and the lack of robustness to outliers. A recent clustering approach proposed a fast search algorithm of cluster centers based on their local densities. However...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280215609948
更新日期:2017-12-01 00:00:00
abstract:BACKGROUND:Recent literature on the comparison of machine learning methods has raised questions about the neutrality, unbiasedness and utility of many comparative studies. Reporting of results on favourable datasets and sampling error in the estimated performance measures based on single samples are thought to be the m...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
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更新日期:2016-10-01 00:00:00
abstract::In this study, we discuss a decision theoretic or fully Bayesian approach to the sample size question in clinical trials with binary responses. Data are assumed to come from two binomial distributions. A Dirichlet distribution is assumed to describe prior knowledge of the two success probabilities p1 and p2. The param...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280211399562
更新日期:2013-12-01 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
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doi:10.1177/0962280212447150
更新日期:2014-04-01 00:00:00
abstract::This paper focuses on inferential tools in the logistic regression model fitted by the Firth penalized likelihood. In this context, the Likelihood Ratio statistic is often reported to be the preferred choice as compared to the 'traditional' Wald statistic. In this work, we consider and discuss a wider range of test st...
journal_title:Statistical methods in medical research
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更新日期:2018-05-01 00:00:00