Multiple imputation by chained equations for data that are missing not at random: methods development for randomised trials and observational studies
通过链式方程对非随机丢失的数据进行多重插补:随机试验和观察性研究的方法开发
基本信息
- 批准号:MC_EX_MR/M025012/1
- 负责人:
- 金额:$ 21.25万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2016
- 资助国家:英国
- 起止时间:2016 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Medical researchers often find that some data which they intended to collect could not be collected: for example, because participants could not be contacted or were unwilling to provide data. These missing data present problems in the analysis of the study, because including only participants who provided data may lead to incorrect results. The commonest way to handle missing data assumes that missing values are similar to observed values within subgroups: for example, for participants whose weight was observed at times 1 and 2 but missing at time 3, the missing weights at time 3 are assumed to have the same average as observed weights at time 3 in participants whose weights were similar at times 1 and 2 and observed at time 3. This approach is called "Missing at Random" and provides a good starting point for analysis but is unlikely to be entirely correct: for example, participants whose weight was unobserved at time 3 may have had a larger weight gain. It is therefore important for researchers to do sensitivity analyses in which different assumptions are made about the missing data. Our research proposes to adapt a popular method for handling missing data called Multiple Imputation by Chained Equations (MICE) to allow for a range of assumptions about the missing data. The idea of this approach is that missing values are filled in iteratively using the relationships between all the variables, and this is then done multiple times in order to express uncertainty about the missing data. However, at present the MICE method is done assuming Missing at Random. We have developed a new way to implement the MICE method which does not assume Missing at Random: instead, the researcher has to specify how big the departures from Missing at Random are, by specifying the likely average differences between missing values and observed values within subgroups. However, we have only explored the new method in idealised settings, and in particular we have not explored its use in randomised trials or in studies where outcomes are measured over time.The work will first extend the statistical theory to handle outcomes that are measured over time and see how well the method performs in randomised trials. It will then extend the methods to tackle a wide range of problems met in practice: for example different types of variables, complex analysis questions, and very large data sets. This work will be supported by writing user-friendly software to implement the new method in two widely used statistics packages. We will implement the method in practice in several data sets, including the Avon Longitudinal Study of Parents and Children where we will explore predictors of self-harm, and randomised trials in smoking cessation and weight loss. Missing self-harm, smoking cessation and weight loss data are all very unlikely to be Missing at Random: we will use our subject matter expertise to specify a range of likely average differences between missing values and observed values within subgroups and hence reach more defensible conclusions. This work is likely to raise unexpected theoretical issues which we will address.Finally, we believe that this method will be widely applicable, so we will disseminate it to researchers via tutorial articles and by running courses.
医学研究人员经常发现他们打算收集的一些数据无法收集:例如,由于无法联系到参与者或不愿意提供数据。这些缺失的数据给研究分析带来了问题,因为只包括提供数据的参与者可能会导致错误的结果。处理缺失数据的最常见方法假设缺失值与亚组内的观察值相似:例如,对于在时间1和2观察到体重但在时间3缺失的受试者,假设在时间3缺失的体重与在时间1和2观察到体重相似且在时间3观察到体重的受试者在时间3观察到的体重具有相同的平均值。这种方法被称为“随机缺失”,为分析提供了一个很好的起点,但不太可能完全正确:例如,在时间3时未观察到体重的参与者可能有更大的体重增加。因此,重要的是研究人员进行敏感性分析,其中对缺失数据做出不同的假设。我们的研究建议采用一种流行的方法来处理缺失数据,称为链式方程多重插补(MICE),以允许对缺失数据进行一系列假设。这种方法的思想是,使用所有变量之间的关系迭代地填充缺失值,然后多次填充,以表示缺失数据的不确定性。然而,目前的MICE方法是假设随机缺失。我们开发了一种新的方法来实现MICE方法,该方法不假设随机缺失:相反,研究人员必须通过指定子组内缺失值和观察值之间的可能平均差异来指定与随机缺失的偏差有多大。然而,我们只在理想化的环境中探索了新方法,特别是我们还没有探索它在随机试验或随时间测量结果的研究中的应用,这项工作将首先扩展统计理论,以处理随时间测量的结果,并看看该方法在随机试验中的表现如何。然后,它将扩展方法,以解决实践中遇到的各种问题:例如不同类型的变量,复杂的分析问题和非常大的数据集。这项工作将得到编写方便用户的软件的支持,以便在两个广泛使用的统计软件包中实施新方法。我们将在几个数据集的实践中实施该方法,包括雅芳父母和儿童纵向研究,我们将探索自我伤害的预测因素,以及戒烟和减肥的随机试验。缺失的自我伤害、戒烟和体重减轻数据都不太可能是随机缺失:我们将使用我们的主题专业知识来指定亚组内缺失值和观察值之间可能的平均差异范围,从而得出更合理的结论。这项工作可能会提出意想不到的理论问题,我们将解决。最后,我们相信这种方法将被广泛应用,所以我们将通过教程文章和运行课程向研究人员传播它。
项目成果
期刊论文数量(7)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Canonical Causal Diagrams to Guide the Treatment of Missing Data in Epidemiologic Studies.
在流行病学研究中指导缺失数据的治疗的规范因果图。
- DOI:10.1093/aje/kwy173
- 发表时间:2018-12-01
- 期刊:
- 影响因子:5
- 作者:Moreno-Betancur M;Lee KJ;Leacy FP;White IR;Simpson JA;Carlin JB
- 通讯作者:Carlin JB
A general method for elicitation, imputation, and sensitivity analysis for incomplete repeated binary data.
- DOI:10.1002/sim.8584
- 发表时间:2020-09-30
- 期刊:
- 影响因子:2
- 作者:Tompsett D;Sutton S;Seaman SR;White IR
- 通讯作者:White IR
The design-by-treatment interaction model: a unifying framework for modelling loop inconsistency in network meta-analysis.
- DOI:10.1002/jrsm.1188
- 发表时间:2016-09
- 期刊:
- 影响因子:9.8
- 作者:Jackson D;Boddington P;White IR
- 通讯作者:White IR
New models for describing outliers in meta-analysis.
- DOI:10.1002/jrsm.1191
- 发表时间:2016-09
- 期刊:
- 影响因子:9.8
- 作者:Baker R;Jackson D
- 通讯作者:Jackson D
On the use of the not-at-random fully conditional specification (NARFCS) procedure in practice.
- DOI:10.1002/sim.7643
- 发表时间:2018-07-10
- 期刊:
- 影响因子:2
- 作者:Tompsett DM;Leacy F;Moreno-Betancur M;Heron J;White IR
- 通讯作者:White IR
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Ian White其他文献
Acceptable risk of contact allergy in the general population assessed by CE–DUR – A method to detect and categorize contact allergy epidemics based on patient data
- DOI:
10.1016/j.yrtph.2009.04.001 - 发表时间:
2009-07-01 - 期刊:
- 影响因子:
- 作者:
Jacob Pontoppidan Thyssen;Torkil Menné;Axel Schnuch;Wolfgang Uter;Ian White;Jonathan M. White;Jeanne Duus Johansen - 通讯作者:
Jeanne Duus Johansen
Inadvertent epidural administration of potassium chloride
- DOI:
10.1007/bf03020353 - 发表时间:
1988-11-01 - 期刊:
- 影响因子:3.300
- 作者:
Michael J. Tessler;Ian White;MaryAnne Naugler-Colville;Diane R. Biehl - 通讯作者:
Diane R. Biehl
Background Little isknown about whatcharacteristics of teams, staff and patients are associatedwith a favourable outcome of severemental illnessmanaged byassertive outreach. Aims Toidentifypredictorsof voluntary and compulsory admissions in routine assertive outreach services in the UK. Method Nine
背景 对于团队、工作人员和患者的哪些特征与积极外展管理的严重精神疾病的良好结果相关,人们知之甚少。
- DOI:
- 发表时间:
2004 - 期刊:
- 影响因子:0
- 作者:
S. Priebe;W. Fakhoury;Ian White;Joanna Watts;P. Bebbington;J. Billings;T. Burns;Sonia Johnson;M. Muijen - 通讯作者:
M. Muijen
Who wants to terminate the game? The role of vested interests and metaplayers in the ATOLLGAME experience
谁想终止游戏?
- DOI:
10.1177/1046878107300673 - 发表时间:
2007 - 期刊:
- 影响因子:2
- 作者:
A. Dray;P. Perez;Christophe Le Page;P. D'Aquino;Ian White - 通讯作者:
Ian White
Response to Limited surface impacts of the January 2021 sudden stratospheric warming
对 2021 年 1 月平流层突然变暖有限地表影响的响应
- DOI:
10.1038/s41467-023-38772-3 - 发表时间:
2023-06-07 - 期刊:
- 影响因子:15.700
- 作者:
Judah Cohen;Laurie Agel;Mathew Barlow;Chaim I. Garfinkel;Ian White - 通讯作者:
Ian White
Ian White的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Ian White', 18)}}的其他基金
REU Site: New approaches to engineering cells, tissues, and organs
REU 网站:工程细胞、组织和器官的新方法
- 批准号:
1757745 - 财政年份:2018
- 资助金额:
$ 21.25万 - 项目类别:
Standard Grant
CAREER: Paper-based surface enhanced Raman spectroscopy (P-SERS) for biosensing using inkjet-fabricated devices
职业:使用喷墨制造设备进行生物传感的纸基表面增强拉曼光谱 (P-SERS)
- 批准号:
1149850 - 财政年份:2012
- 资助金额:
$ 21.25万 - 项目类别:
Standard Grant
SBIR Phase I: Extension of Multiphoton Polymerization fabrication technology to the fabrication of Retinal Image Management (RIM) elements
SBIR 第一阶段:将多光子聚合制造技术扩展到视网膜图像管理 (RIM) 元件的制造
- 批准号:
0638051 - 财政年份:2007
- 资助金额:
$ 21.25万 - 项目类别:
Standard Grant
SBIR Phase I: Spatially selective metallization of microfabricated 3D structures and lines using Multiphoton Polymerization (MPP) for optical, photonic and electrical micro-systems
SBIR 第一阶段:使用多光子聚合 (MPP) 对光学、光子和电气微系统进行微加工 3D 结构和线条的空间选择性金属化
- 批准号:
0638055 - 财政年份:2007
- 资助金额:
$ 21.25万 - 项目类别:
Standard Grant
SBIR Phase I: Simulation Model for Two-Photon Absorption Fabricated Microstructures
SBIR 第一阶段:双光子吸收制造微结构的仿真模型
- 批准号:
0512759 - 财政年份:2005
- 资助金额:
$ 21.25万 - 项目类别:
Standard Grant
相似国自然基金
利用Imputation和Meta分析方法深度搜寻IgA肾病新的易感基因
- 批准号:81570599
- 批准年份:2015
- 资助金额:57.0 万元
- 项目类别:面上项目
数据缺失时高维数据降维分析的方法、理论与应用
- 批准号:11171331
- 批准年份:2011
- 资助金额:40.0 万元
- 项目类别:面上项目
Imputation法及其在MHC区域易感基因搜寻中的应用
- 批准号:31000528
- 批准年份:2010
- 资助金额:19.0 万元
- 项目类别:青年科学基金项目
相似海外基金
IMR: MM-1C: Fine-grained Network Monitoring via Software Imputation
IMR:MM-1C:通过软件插补进行细粒度网络监控
- 批准号:
2319442 - 财政年份:2023
- 资助金额:
$ 21.25万 - 项目类别:
Standard Grant
Mendelian imputation for family-based GWAS and association-by-proxy in diverse ancestries
基于家庭的 GWAS 和不同祖先的代理关联的孟德尔插补
- 批准号:
10717993 - 财政年份:2023
- 资助金额:
$ 21.25万 - 项目类别:
Secure Outsourcing of Genotype Imputation for Privacy-aware Genomic Analysis (RO1HE21)
用于隐私意识基因组分析的基因型插补的安全外包 (RO1HE21)
- 批准号:
10587347 - 财政年份:2023
- 资助金额:
$ 21.25万 - 项目类别:
Research on imputation methods for missing values in real world data
现实数据缺失值插补方法研究
- 批准号:
23K11011 - 财政年份:2023
- 资助金额:
$ 21.25万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Bioinformatic investigation of previously neglected regions of the genome and their association with age-related hearing loss
对以前被忽视的基因组区域及其与年龄相关性听力损失的关联进行生物信息学研究
- 批准号:
481299 - 财政年份:2022
- 资助金额:
$ 21.25万 - 项目类别:
Operating Grants
Improving the robustness of chained equation imputation by incorporating compatibility blocks
通过合并兼容性块来提高链式方程插补的鲁棒性
- 批准号:
559849-2021 - 财政年份:2022
- 资助金额:
$ 21.25万 - 项目类别:
Alexander Graham Bell Canada Graduate Scholarships - Doctoral
Imputation multiple pour de l'inférence sur une Anova
方差分析的多重插补
- 批准号:
574038-2022 - 财政年份:2022
- 资助金额:
$ 21.25万 - 项目类别:
University Undergraduate Student Research Awards
Time Series and Spectral Methods for Imputation, Regression, and Environmental Health
用于插补、回归和环境健康的时间序列和谱方法
- 批准号:
RGPIN-2017-04741 - 财政年份:2022
- 资助金额:
$ 21.25万 - 项目类别:
Discovery Grants Program - Individual
Novel statistical methods for transcriptomic imputation to enhance understanding of causal mechanisms underlying human diseases
转录组插补的新统计方法可增强对人类疾病因果机制的理解
- 批准号:
MR/V020749/1 - 财政年份:2022
- 资助金额:
$ 21.25万 - 项目类别:
Research Grant
Variance estimation under multiple imputation for missing survey data
缺失调查数据多重插补下的方差估计
- 批准号:
574963-2022 - 财政年份:2022
- 资助金额:
$ 21.25万 - 项目类别:
University Undergraduate Student Research Awards