Methods for causal analysis of longitudinal data

纵向数据因果分析方法

基本信息

  • 批准号:
    402474-2011
  • 负责人:
  • 金额:
    $ 1.24万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2013
  • 资助国家:
    加拿大
  • 起止时间:
    2013-01-01 至 2014-12-31
  • 项目状态:
    已结题

项目摘要

One of the most fundamental questions in medical and health research is: "Does using a particular treatment make sick patients live longer?" In some settings this question can be addressed through the use of a randomized trial however such trials are very expensive and may take many years to complete. An alternative is to try and answer the question using what is known as observational data. That is, data available from completed studies, registries or databases in which the treatment outcome, and a set of patient characteristics have been recorded for a group of subjects. This research program is focused on settings in which treatment is dynamic and changing over time. For example, the dose of a drug that a patient is given over their course of treatment. We assume that subjects receive treatment at regularly spaced intervals (days, weeks, months, etc.) and that as time progresses the level and/or type of treatment they receive is based on their growing history of observed characteristics. A treatment regimen is a rule describing how their next treatment level is determined. Examples of such settings include rules for epoetin dosing to treat anemia in dialysis patients and post-surgical blood transfusion treatment for cardiac patients. This research program is focused on developing statistical models and methods that allow for valid comparison of treatment regimens based on observational data.
医学和健康研究中最基本的问题之一是:“使用某种特定的治疗方法是否会使病人活得更长?“在某些情况下,这个问题可以通过使用随机试验来解决,但这种试验非常昂贵,可能需要多年才能完成。另一种方法是尝试使用所谓的观测数据来回答这个问题。即,已完成研究、登记研究或数据库中的可用数据,其中记录了一组受试者的治疗结局和一组患者特征。该研究计划的重点是治疗是动态的,并随着时间的推移而变化的设置。例如,在治疗过程中给予患者的药物剂量。我们假设受试者以规则间隔(天、周、月等)接受治疗。并且随着时间的推移,他们所接受的治疗的水平和/或类型是基于他们所观察到的特征的生长历史。治疗方案是描述如何确定下一个治疗水平的规则。此类设置的示例包括用于治疗透析患者贫血的依泊苷给药规则和用于心脏病患者的术后输血治疗。该研究项目的重点是开发统计模型和方法,以便根据观察数据对治疗方案进行有效比较。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ 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 }}

Cotton, Cecilia其他文献

Correlates of Opioid Use Among Ontario Long-Term Care Residents and Variation by Pain Frequency and Intensity: A Cross-sectional Analysis.
  • DOI:
    10.1007/s40266-022-00972-9
  • 发表时间:
    2022-10
  • 期刊:
  • 影响因子:
    2.8
  • 作者:
    Iacono, Anita;Campitelli, Michael A.;Bronskill, Susan E.;Hogan, David B.;Iaboni, Andrea;Maclagan, Laura C.;Gomes, Tara;Tadrous, Mina;Evans, Charity;Gruneir, Andrea;Guan, Qi;Hadjistavropoulos, Thomas;Cotton, Cecilia;Gill, Sudeep S.;Seitz, Dallas P.;Ho, Joanne;Maxwell, Colleen J.
  • 通讯作者:
    Maxwell, Colleen J.
Impact of Early Breast Cancer Screening on Mortality Among Young Survivors of Childhood Hodgkin's Lymphoma

Cotton, Cecilia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('Cotton, Cecilia', 18)}}的其他基金

Methods for causal analysis of longitudinal data
纵向数据因果分析方法
  • 批准号:
    RGPIN-2019-04174
  • 财政年份:
    2022
  • 资助金额:
    $ 1.24万
  • 项目类别:
    Discovery Grants Program - Individual
Methods for causal analysis of longitudinal data
纵向数据因果分析方法
  • 批准号:
    RGPIN-2019-04174
  • 财政年份:
    2021
  • 资助金额:
    $ 1.24万
  • 项目类别:
    Discovery Grants Program - Individual
Methods for causal analysis of longitudinal data
纵向数据因果分析方法
  • 批准号:
    RGPIN-2019-04174
  • 财政年份:
    2020
  • 资助金额:
    $ 1.24万
  • 项目类别:
    Discovery Grants Program - Individual
Methods for causal analysis of longitudinal data
纵向数据因果分析方法
  • 批准号:
    RGPIN-2019-04174
  • 财政年份:
    2019
  • 资助金额:
    $ 1.24万
  • 项目类别:
    Discovery Grants Program - Individual
Methods for causal analysis of longitudinal data
纵向数据因果分析方法
  • 批准号:
    402474-2011
  • 财政年份:
    2018
  • 资助金额:
    $ 1.24万
  • 项目类别:
    Discovery Grants Program - Individual
Methods for causal analysis of longitudinal data
纵向数据因果分析方法
  • 批准号:
    402474-2011
  • 财政年份:
    2017
  • 资助金额:
    $ 1.24万
  • 项目类别:
    Discovery Grants Program - Individual
Methods for causal analysis of longitudinal data
纵向数据因果分析方法
  • 批准号:
    402474-2011
  • 财政年份:
    2014
  • 资助金额:
    $ 1.24万
  • 项目类别:
    Discovery Grants Program - Individual
Methods for causal analysis of longitudinal data
纵向数据因果分析方法
  • 批准号:
    402474-2011
  • 财政年份:
    2012
  • 资助金额:
    $ 1.24万
  • 项目类别:
    Discovery Grants Program - Individual
Methods for causal analysis of longitudinal data
纵向数据因果分析方法
  • 批准号:
    402474-2011
  • 财政年份:
    2011
  • 资助金额:
    $ 1.24万
  • 项目类别:
    Discovery Grants Program - Individual
PGSA
前列腺素A
  • 批准号:
    255289-2002
  • 财政年份:
    2002
  • 资助金额:
    $ 1.24万
  • 项目类别:
    Postgraduate Scholarships

相似国自然基金

使用倾向分(Propensity Score)和主分层(Principal Stratification)进行因果推断
  • 批准号:
    10401003
  • 批准年份:
    2004
  • 资助金额:
    11.0 万元
  • 项目类别:
    青年科学基金项目

相似海外基金

The contribution of air pollution to racial and ethnic disparities in Alzheimer’s disease and related dementias: An application of causal inference methods
空气污染对阿尔茨海默病和相关痴呆症的种族和民族差异的影响:因果推理方法的应用
  • 批准号:
    10642607
  • 财政年份:
    2023
  • 资助金额:
    $ 1.24万
  • 项目类别:
Leveraging Causal Inference and Machine Learning Methods to Advance Evidence-Based Maternal Care and Improve Newborn Health Outcomes
利用因果推理和机器学习方法推进循证孕产妇护理并改善新生儿健康结果
  • 批准号:
    10604856
  • 财政年份:
    2023
  • 资助金额:
    $ 1.24万
  • 项目类别:
Multiomics data integration methods to discover putative causal variants, genes and patient heterogeneity for Alzheimers disease
多组学数据整合方法发现阿尔茨海默病的假定因果变异、基因和患者异质性
  • 批准号:
    10587524
  • 财政年份:
    2023
  • 资助金额:
    $ 1.24万
  • 项目类别:
Using Causal Machine Learning Methods to Inform Tobacco Regulatory Science
使用因果机器学习方法为烟草监管科学提供信息
  • 批准号:
    10662955
  • 财政年份:
    2023
  • 资助金额:
    $ 1.24万
  • 项目类别:
Statistical Methods for Data Integration and Applications to Genome-wide Association Studies
数据集成的统计方法及其在全基因组关联研究中的应用
  • 批准号:
    10889298
  • 财政年份:
    2023
  • 资助金额:
    $ 1.24万
  • 项目类别:
Computational methods to elucidate the role of long non-coding RNA in Congenital Heart Disease
阐明长非编码RNA在先天性心脏病中作用的计算方法
  • 批准号:
    10680021
  • 财政年份:
    2023
  • 资助金额:
    $ 1.24万
  • 项目类别:
Statistical methods to characterize causal mechanisms by which air pollution affects the recurrence of cardiovascular events
描述空气污染影响心血管事件复发因果机制的统计方法
  • 批准号:
    10660281
  • 财政年份:
    2023
  • 资助金额:
    $ 1.24万
  • 项目类别:
Development of High-Precision Geospatial Information Utilization Methods in Urban and Regional Economic Analysis and Their Application to Spatial Causal Inference
城市和区域经济分析中高精度地理空间信息利用方法的发展及其在空间因果推理中的应用
  • 批准号:
    23K17559
  • 财政年份:
    2023
  • 资助金额:
    $ 1.24万
  • 项目类别:
    Grant-in-Aid for Challenging Research (Exploratory)
Developing causal inference methods to evaluate and leverage spillover effects through social Interactions for designing improved HIV prevention interventions
开发因果推理方法,通过社会互动评估和利用溢出效应,设计改进的艾滋病毒预防干预措施
  • 批准号:
    10762679
  • 财政年份:
    2023
  • 资助金额:
    $ 1.24万
  • 项目类别:
Improving Methods and Practices for Trans-Ethnic Genetic Studies
改进跨种族遗传研究的方法和实践
  • 批准号:
    10584152
  • 财政年份:
    2023
  • 资助金额:
    $ 1.24万
  • 项目类别:
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了