对比两种基于倾向分数的方法来平衡共变量:重叠权重和细分分层方法在现实世界索赔数据中的比较
Wen Wan1, Manoradhan Murugesan2, Robert S Nocon3
1Section of General Internal Medicine, Department of Medicine, The University of Chicago, 5841 S. Maryland Ave, Chicago, MC, IL, 2007, 60637, USA. wwan1@medicine.bsd.uchicago.edu.
BMC medical research methodology
|June 3, 2024
概括
与细分分层 (FS) 相比,重叠权重 (OW) 方法提供了优越的共变量平衡,提高了大索赔数据中的平均治疗效果估计,具有低患病率暴露和低频率结果.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 倾向分数 (PS) 方法,如重叠加权 (OW) 和细分分层 (FS) 实现了优异的共变量平衡.
- OW与其他权重方法进行比较,FS与分层和匹配方法进行比较.
- 没有研究直接比较OW和FS,特别是在具有低患病率暴露和低频率结果的大型索赔数据中.
研究的目的:
- 为了比较重叠加权重 (OW) 和细分分层 (FS) 方法的性能.
- 评估OW和FS在大型索赔数据中,其特点是患病率低的暴露和低频率的结果.
- 评估共变量平衡和平均治疗效果估计的准确性.
主要方法:
- 使用德克萨斯州医疗补助申请数据 (N=42,628) 对于2012年糖尿病成年受益者.
- 使用加权通用线性模型估计卫生中心出勤的平均治疗效应.
- 使用等离子模式方法进行模拟 (N=4,000) 以评估在各种条件下的相对性能.
主要成果:
- 在经验实例中,OW 显示出优异的协变平衡,标准化平均差异和Mahalanobis平衡距离 (MB) 比FS小.
- 在模拟中,OW与FS相比,始终实现了更小的MB,相对偏差,以及更好的平方根平均平方误差和覆盖概率.
- 在各种模拟场景中,OW产生了几乎完美的共变量平衡.
结论:
- 叠加权重 (OW) 在实现优异的共变量平衡方面非常有效.
- OW提高了平均治疗效果估计的准确性,特别是在具有挑战性的数据设置中.
- OW是一种推的方法,用于分析具有低患病率暴露率和低频率结果的大型索赔数据.
相关概念视频
01:25Strategies for Assessing and Addressing Confounding
92
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
92
01:20Comparing the Survival Analysis of Two or More Groups
177
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
177
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
125
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
125
01:16Stratified Sampling Method
12.0K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
To choose a stratified sample, divide the population into groups called strata and then take a...
12.0K
01:13Randomized Experiments
6.9K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Simple randomization
Simple...
6.9K
01:24Testing a Claim about Population Proportion
3.3K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
3.3K