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 studies. Although a variety of methods have been proposed, they are very rarely used in practice. To stimulate their use and further development, this article provides a comprehensive overview on methods developed for multivariable regression analysis of epidemiologic studies with validation data sets. The methods are systematically classified with respect to the underlying theory. An assessment of prerequisites, assumptions and performance of the available methods is given. Particular attention is paid to applicability to case-control studies and need for further research and development is pointed out.
journal_name
Stat Methods Med Resjournal_title
Statistical methods in medical researchauthors
Thürigen D,Spiegelman D,Blettner M,Heuer C,Brenner Hdoi
10.1177/096228020000900504subject
Has Abstractpub_date
2000-10-01 00:00:00pages
447-74issue
5eissn
0962-2802issn
1477-0334journal_volume
9pub_type
杂志文章,评审abstract::Rapid Early Action for Coronary Treatment (REACT) was a multisite trial testing a community intervention to reduce the delay between onset of symptoms of acute myocardial infarction (MI) and patients' arrival at a hospital emergency department. The study employed a group-randomized trial design, with ten communities r...
journal_title:Statistical methods in medical research
pub_type: 临床试验,杂志文章,随机对照试验
doi:10.1177/096228020000900204
更新日期:2000-04-01 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::The analysis of fecundity data is challenging and requires consideration of both highly timed and interrelated biologic processes in the context of essential behaviors such as sexual intercourse during the fertile window. Understanding human fecundity is further complicated by presence of a sterile population, i.e. co...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280212438646
更新日期:2016-02-01 00:00:00
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::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::Age-period-cohort models are a popular tool for studying population-level rates; for example, trends in cancer incidence and mortality. Age-period-cohort models decompose observed trends into age effects that correlate with natural history, period effects that reveal factors impacting all ages simultaneously (e.g. inn...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217713033
更新日期:2019-01-01 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::A dynamic treatment regime is a set of decision rules for how to treat a patient at multiple time points. At each time point, a treatment decision is made depending on the patient's medical history up to that point. We consider the infinite-horizon setting in which the number of decision points is very large. Specific...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217708655
更新日期:2017-08-01 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
doi:10.1177/0962280213502437
更新日期:2016-10-01 00:00:00
abstract::Ordinal classification scales are commonly used to define a patient's disease status in screening and diagnostic tests such as mammography. Challenges arise in agreement studies when evaluating the association between many raters' classifications of patients' disease or health status when an ordered categorical scale ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280216643347
更新日期:2018-03-01 00:00:00
abstract::The use of genetic variants as instrumental variables - an approach known as Mendelian randomization - is a popular epidemiological method for estimating the causal effect of an exposure (phenotype, biomarker, risk factor) on a disease or health-related outcome from observational data. Instrumental variables must sati...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219851817
更新日期:2020-04-01 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::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 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::Pattern-mixture model (PMM)-based controlled imputations have become a popular tool to assess the sensitivity of primary analysis inference to different post-dropout assumptions or to estimate treatment effectiveness. The methodology is well established for continuous responses but less well established for binary res...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280220941880
更新日期:2020-12-01 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
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::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::Aim To present a flexible model for repeated measures longitudinal growth data within individuals that allows trends over time to incorporate individual-specific random effects. These may reflect the timing of growth events and characterise within-individual variability which can be modelled as a function of age. Subj...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217706728
更新日期:2018-11-01 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
pub_type: 杂志文章
doi:10.1177/0962280218784726
更新日期:2019-08-01 00:00:00
abstract::Statistical methods for spatial health data to identify the significant covariates associated with the health outcomes are of critical importance. Most studies have developed variable selection approaches in which the covariates included appear within the spatial domain and their effects are fixed across space. Howeve...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280215627184
更新日期:2018-01-01 00:00:00
abstract::Monte Carlo evaluation of resampling-based tests is often conducted in statistical analysis. However, this procedure is generally computationally intensive. The pooling resampling-based method has been developed to reduce the computational burden but the validity of the method has not been studied before. In this arti...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280216661876
更新日期:2018-05-01 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::Evaluation of medical imaging devices often involves clinical studies where multiple readers (MR) read images of multiple cases (MC) for a clinical task, which are often called MRMC studies. In addition to sizing patient cases as is required in most clinical trials, MRMC studies also require sizing readers, since both...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219869370
更新日期:2020-06-01 00:00:00
abstract::We propose a cross-validated area under the receiving operator characteristic (ROC) curve (CV-AUC) criterion for tuning parameter selection for penalized methods in sparse, high-dimensional logistic regression models. We use this criterion in combination with the minimax concave penalty (MCP) method for variable selec...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280211428385
更新日期:2013-10-01 00:00:00
abstract::Recently, the joint analysis of longitudinal and survival data has been an active research area. Most joint models focus on survival data with only one type of failure. The research on joint modeling of longitudinal and competing risks survival data is sparse. Even so, many joint models for this type of data assume pa...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280215597939
更新日期:2017-10-01 00:00:00
abstract::This article is motivated by jointly modelling longitudinal and time-to-event clinical data of patients with diabetes and end-stage renal disease. All patients are on the waiting list for the pancreas transplant after kidney transplant, and some of them have a pancreas transplant before kidney transplant failure or de...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218786980
更新日期:2019-09-01 00:00:00
abstract::Propensity score methods are common for estimating a binary treatment effect when treatment assignment is not randomized. When exposure is measured on an ordinal scale (i.e. low-medium-high), however, propensity score inference requires extensions which have received limited attention. Estimands of possible interest w...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214560046
更新日期:2017-04-01 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::This article outlines the statistical developments that have taken place in the use of the EM algorithm in emission and transmission tomography during the past decade or so. We discuss the statistical aspects of the modelling of the projection data for both the emission and transmission cases and define the relevant p...
journal_title:Statistical methods in medical research
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