Abstract:
:Agreement between two methods of clinical measurement can be quantified using the differences between observations made using the two methods on the same subjects. The 95% limits of agreement, estimated by mean difference +/- 1.96 standard deviation of the differences, provide an interval within which 95% of differences between measurements by the two methods are expected to lie. We describe how graphical methods can be used to investigate the assumptions of the method and we also give confidence intervals. We extend the basic approach to data where there is a relationship between difference and magnitude, both with a simple logarithmic transformation approach and a new, more general, regression approach. We discuss the importance of the repeatability of each method separately and compare an estimate of this to the limits of agreement. We extend the limits of agreement approach to data with repeated measurements, proposing new estimates for equal numbers of replicates by each method on each subject, for unequal numbers of replicates, and for replicated data collected in pairs, where the underlying value of the quantity being measured is changing. Finally, we describe a nonparametric approach to comparing methods.
journal_name
Stat Methods Med Resjournal_title
Statistical methods in medical researchauthors
Bland JM,Altman DGdoi
10.1177/096228029900800204subject
Has Abstractpub_date
1999-06-01 00:00:00pages
135-60issue
2eissn
0962-2802issn
1477-0334journal_volume
8pub_type
杂志文章,评审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
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journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219865579
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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::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
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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...
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doi:10.1177/0962280217718867
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abstract::Joint modelling of longitudinal biomarker and event-time processes has gained its popularity in recent years as they yield more accurate and precise estimates. Considering this modelling framework, a new methodology for evaluating the time-dependent efficacy of a longitudinal biomarker for clinical endpoint is propose...
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doi:10.1177/0962280216673084
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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...
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pub_type: 杂志文章,评审
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更新日期:1992-01-01 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...
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pub_type: 杂志文章,评审
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更新日期:1998-06-01 00:00:00
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doi:10.1177/0962280207081860
更新日期:2008-10-01 00:00:00
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pub_type: 杂志文章
doi:10.1191/0962280205sm413oa
更新日期:2005-10-01 00:00:00
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journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217690770
更新日期:2018-10-01 00:00:00
abstract::The maximal procedure is a restricted randomization method that maximizes the number of feasible allocation sequences under the constraints of the maximum tolerated imbalance and the allocation sequence length. It assigns an equal probability to all feasible sequences. However, its implementation is not easy due to th...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280216677107
更新日期:2018-07-01 00:00:00
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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::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
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journal_title:Statistical methods in medical research
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doi:10.1177/0962280220951834
更新日期:2020-09-25 00:00:00
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::Multilevel models were originally developed to allow linear regression or ANOVA models to be applied to observations that are not mutually independent. This lack of independence commonly arises due to clustering of the units of observations into 'higher level units' such as patients in hospitals. In linear mixed model...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/096228020101000604
更新日期:2001-12-01 00:00:00
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doi:10.1177/0962280214544207
更新日期:2017-02-01 00:00:00
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pub_type: 杂志文章
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journal_title:Statistical methods in medical research
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doi:10.1177/0962280210370265
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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
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journal_title:Statistical methods in medical research
pub_type: 评论,信件
doi:10.1177/0962280217712089
更新日期:2018-12-01 00:00:00
abstract::Censored data make survival analysis more complicated because exact event times are not observed. Statistical methodology developed to account for censored observations assumes that patients' withdrawal from a study is independent of the event of interest. However, in practice, some covariates might be associated to b...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280216628900
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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
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更新日期:2020-12-01 00:00:00
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journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1191/0962280204sm352ra
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journal_title:Statistical methods in medical research
pub_type: 传,历史文章,杂志文章,评审
doi:10.1177/096228029700600202
更新日期:1997-06-01 00:00:00
abstract::Two tests are proposed for checking the linearity of nonparametric function in partially linear models. The first one is based on a Crámer-von Mises statistic. This test can detect the local alternative converging to the null at the parametric rate 1/square root n. A bootstrap resample technique is provided to calcula...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1191/0962280206sm440oa
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journal_title:Statistical methods in medical research
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