Journal of Causal Inference最新文献

Evaluating Boolean relationships in Configurational Comparative Methods 在配置比较法中评估布尔关系

IF 1.4 4区医学

Journal of Causal Inference Pub Date : 2024-01-01 DOI: 10.1515/jci-2023-0014

Luna De Souter

{"title":"Evaluating Boolean relationships in Configurational Comparative Methods","authors":"Luna De Souter","doi":"10.1515/jci-2023-0014","DOIUrl":"https://doi.org/10.1515/jci-2023-0014","url":null,"abstract":"Abstract Configurational Comparative Methods (CCMs) aim to learn causal structures from datasets by exploiting Boolean sufficiency and necessity relationships. One important challenge for these methods is that such Boolean relationships are often not satisfied in real-life datasets, as these datasets usually contain noise. Hence, CCMs infer models that only approximately fit the data, introducing a risk of inferring incorrect or incomplete models, especially when data are also fragmented (have limited empirical diversity). To minimize this risk, evaluation measures for sufficiency and necessity should be sensitive to all relevant evidence. This article points out that the standard evaluation measures in CCMs, consistency and coverage, neglect certain evidence for these Boolean relationships. Correspondingly, two new measures, contrapositive consistency and contrapositive coverage, which are equivalent to the binary classification measures specificity and negative predictive value, respectively, are introduced to the CCM context as additions to consistency and coverage. A simulation experiment demonstrates that the introduced contrapositive measures indeed help to identify correct CCM models.","PeriodicalId":48576,"journal":{"name":"Journal of Causal Inference","volume":"8 12","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139457038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparison of open-source software for producing directed acyclic graphs. 制作有向无环图的开源软件比较。

IF 1.4 4区医学

Journal of Causal Inference Pub Date : 2024-01-01 Epub Date: 2024-01-10 DOI: 10.1515/jci-2023-0031

Amy J Pitts, Charlotte R Fowler

引用次数: 0

LINGUISTIC FEATURES AND PRESENTATION OF MATERIALS ON ENGLISH TEXTBOOK “WHEN ENGLISH RINGS A BELL” BASED ON BSNP 基于BSNP的英语教材《当英语响铃》的语言特征及材料呈现

4区医学

Journal of Causal Inference Pub Date : 2023-06-17 DOI: 10.30998/inference.v5i3.12353

Hilda Zubaidah, Gustaman Saragih

{"title":"LINGUISTIC FEATURES AND PRESENTATION OF MATERIALS ON ENGLISH TEXTBOOK “WHEN ENGLISH RINGS A BELL” BASED ON BSNP","authors":"Hilda Zubaidah, Gustaman Saragih","doi":"10.30998/inference.v5i3.12353","DOIUrl":"https://doi.org/10.30998/inference.v5i3.12353","url":null,"abstract":"The textbooks play an important role in teaching and learning activity in language program. Because of the various textbooks provided, textbook analysis is seen as an important thing to be conducted in order to find out how the components of the textbook are served. This study was aimed to investigate to what extent the English textbook entitled “Bahasa Inggris: When English Rings a Bell” for eighth grade students meet the criteria of BSNP (linguistic features and presentation of materias). The linguistic features consist of language appropriateness while the presentation of materials consist of content appropriates, presentation appropriateness, and graphic appropriateness. This study was descriptive qualitative approach. The instrument used to collect the data is document study used in the form of checklist. A checklist was made adopted from BSNP (2011) framework. The results of this study showed that textbook entitled “When English Rings a Bell” for Eight Grade is suitable to be used in teaching learning process. The textbook achieved the fulfilment score of language appropriateness (100%), content appropriateness (81,25%), presentation appropriateness (88,89%), and graphics appropriateness (97,64%). This book is categorized “good” textbook by achieving the score of 95,07%. Thus, it can be concluded that textbook is suitable to be used in order to help the teaching learning process in the classroom with the help of other sources and teacher improvisation.","PeriodicalId":48576,"journal":{"name":"Journal of Causal Inference","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135525979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bounding the probabilities of benefit and harm through sensitivity parameters and proxies 通过敏感性参数和代理来确定收益和损害的概率

IF 1.4 4区医学

Journal of Causal Inference Pub Date : 2023-01-01 DOI: 10.48550/arXiv.2303.05396

J. Peña

引用次数: 1

Efficient and flexible mediation analysis with time-varying mediators, treatments, and confounders 具有时变介质、治疗和混杂因素的有效和灵活的中介分析

IF 1.4 4区医学

Journal of Causal Inference Pub Date : 2023-01-01 DOI: 10.1515/jci-2022-0077

Iván Díaz, Nicholas T Williams, K. Rudolph

{"title":"Efficient and flexible mediation analysis with time-varying mediators, treatments, and confounders","authors":"Iván Díaz, Nicholas T Williams, K. Rudolph","doi":"10.1515/jci-2022-0077","DOIUrl":"https://doi.org/10.1515/jci-2022-0077","url":null,"abstract":"Abstract Understanding the mechanisms of action of interventions is a major general goal of scientific inquiry. The collection of statistical methods that use data to achieve this goal is referred to as mediation analysis. Natural direct and indirect effects provide a definition of mediation that matches scientific intuition, but they are not identified in the presence of time-varying confounding. Interventional effects have been proposed as a solution to this problem, but existing estimation methods are limited to assuming simple (e.g., linear) and unrealistic relations between the mediators, treatments, and confounders. We present an identification result for interventional effects in a general longitudinal data structure that allows flexibility in the specification of treatment-outcome, treatment-mediator, and mediator-outcome relationships. Identification is achieved under the standard no-unmeasured-confounders and positivity assumptions. In this article, we study semi-parametric efficiency theory for the functional identifying the mediation parameter, including the non-parametric efficiency bound, and was used to propose non-parametrically efficient estimators. Implementation of our estimators only relies on the availability of regression algorithms, and the estimators in a general framework that allows the analyst to use arbitrary regression machinery were developed. The estimators are doubly robust, n sqrt{n} -consistent, asymptotically Gaussian, under slow convergence rates for the regression algorithms used. This allows the use of flexible machine learning for regression while permitting uncertainty quantification through confidence intervals and p p -values. A free and open-source R package implementing the methods is available on GitHub. The proposed estimator to a motivating example from a trial of two medications for opioid-use disorder was applied, where we estimate the extent to which differences between the two treatments on risk of opioid use are mediated by craving symptoms.","PeriodicalId":48576,"journal":{"name":"Journal of Causal Inference","volume":"10 2 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88192318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification of in-sample positivity violations using regression trees: The PoRT algorithm 使用回归树识别样本内阳性违规:PoRT算法

4区医学

Journal of Causal Inference Pub Date : 2023-01-01 DOI: 10.1515/jci-2022-0032

Gabriel Danelian, Yohann Foucher, Maxime Léger, Florent Le Borgne, Arthur Chatton

引用次数: 0

Personalized decision making – A conceptual introduction 个性化决策-概念介绍

4区医学

Journal of Causal Inference Pub Date : 2023-01-01 DOI: 10.1515/jci-2022-0050

Scott Mueller, Judea Pearl

引用次数: 3

Minimally capturing heterogeneous complier effect of endogenous treatment for any outcome variable 最小限度地捕获内源性治疗对任何结果变量的异质编译效应

IF 1.4 4区医学

Journal of Causal Inference Pub Date : 2023-01-01 DOI: 10.1515/jci-2022-0036

Goeun Lee, Jin‐young Choi, Myoung‐jae Lee

{"title":"Minimally capturing heterogeneous complier effect of endogenous treatment for any outcome variable","authors":"Goeun Lee, Jin‐young Choi, Myoung‐jae Lee","doi":"10.1515/jci-2022-0036","DOIUrl":"https://doi.org/10.1515/jci-2022-0036","url":null,"abstract":"Abstract When a binary treatment D D is possibly endogenous, a binary instrument δ delta is often used to identify the “effect on compliers.” If covariates X X affect both D D and an outcome Y Y , X X should be controlled to identify the “ X X -conditional complier effect.” However, its nonparametric estimation leads to the well-known dimension problem. To avoid this problem while capturing the effect heterogeneity, we identify the complier effect heterogeneous with respect to only the one-dimensional “instrument score” E ( δ ∣ X ) Eleft(delta | X) for non-randomized δ delta . This effect heterogeneity is minimal, in the sense that any other “balancing score” is finer than the instrument score. We establish two critical “reduced-form models” that are linear in D D or δ delta , even though no parametric assumption is imposed. The models hold for any form of Y Y (continuous, binary, count, …). The desired effect is then estimated using either single index model estimators or an instrumental variable estimator after applying a power approximation to the effect. Simulation and empirical studies are performed to illustrate the proposed approaches.","PeriodicalId":48576,"journal":{"name":"Journal of Causal Inference","volume":"8 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83418174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Heterogeneous interventional effects with multiple mediators: Semiparametric and nonparametric approaches 多介质的异质介入效应:半参数和非参数方法

IF 1.4 4区医学

Journal of Causal Inference Pub Date : 2023-01-01 DOI: 10.1515/jci-2022-0070

Max Rubinstein, Zach Branson, Edward Kennedy

{"title":"Heterogeneous interventional effects with multiple mediators: Semiparametric and nonparametric approaches","authors":"Max Rubinstein, Zach Branson, Edward Kennedy","doi":"10.1515/jci-2022-0070","DOIUrl":"https://doi.org/10.1515/jci-2022-0070","url":null,"abstract":"Abstract We propose semiparametric and nonparametric methods to estimate conditional interventional indirect effects in the setting of two discrete mediators whose causal ordering is unknown. Average interventional indirect effects have been shown to decompose an average treatment effect into a direct effect and interventional indirect effects that quantify effects of hypothetical interventions on mediator distributions. Yet these effects may be heterogeneous across the covariate distribution. We consider the problem of estimating these effects at particular points. We propose an influence function-based estimator of the projection of the conditional effects onto a working model, and show under some conditions that we can achieve root-n consistent and asymptotically normal estimates. Second, we propose a fully nonparametric approach to estimation and show the conditions where this approach can achieve oracle rates of convergence. Finally, we propose a sensitivity analysis that identifies bounds on both the average and conditional effects in the presence of mediator-outcome confounding. We show that the same methods easily extend to allow estimation of these bounds. We conclude by examining heterogeneous effects with respect to the effect of COVID-19 vaccinations on depression during February 2021.","PeriodicalId":48576,"journal":{"name":"Journal of Causal Inference","volume":"23 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74453037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Potential outcome and decision theoretic foundations for statistical causality 统计因果关系的潜在结果和决策理论基础

4区医学

Journal of Causal Inference Pub Date : 2023-01-01 DOI: 10.1515/jci-2022-0012

Thomas S. Richardson, James M. Robins

引用次数: 2