GetPortalImpactFactorByIdResp(projectId=1, id=bfe116607, cover=https://img.medsci.cn/2020622/1592791763223_4754896.jpg, fullname=Journal of Causal Inference, abbr=J CAUSAL INFERENCE, pyear=暂无数据, frequence=H, articleNumbers=412, citedSelf2015=null, acceptanceRate=null, submissionToAcceptance=null, averageReviewTime=暂无数据, reviewFee=null, pageFee=null, publishedRatio=, issn=2193-3677, greenSci=https://www.greensci.net/search?kw=2193-3677, scijournal=https://www.scijournal.org/impact-factor-of-J-CAUSAL-INFERENCE.shtml, medsciHotlightString=null, medsciHotlightRealtime=0.983, medsciHotlight=0.562, medsciHotlight5year=0.250667, citescore=1.9, hIndex=9, impactFactor=1.4, orgnization=Walter de Gruyter GmbH, orgnizationUrl=https://www.degruyter.com/, country=Germany, countryCn=德国, isOa=1, isOaString=是, sciScie=Cabell's Whitelist|Case|CNKI Scholar|CNPIEC - cnpLINKer|MedSci|Dimensions|EBSCO (relevant databases)|EconBiz|Genamics |google Scholar|Japan Science and Technology Agency (JST)|J-Gate|Journal Citation Reports/Social Sciences Edition, bigclassCas=null, smallclassCas=医学 4 区, website=http://www.degruyter.com/view/j/jci, websiteHits=401, guideForAuthor=https://www.degruyter.com/supplemental/journals/jci/jci-overview.xml/Instruction_for_Authors.pdf, guideForAuthorHits=136, submitWebsite=https://mc.manuscriptcentral.com/dgjci, submitWebsiteHits=165, content=<p style="color: #3c3c3c;">Journal of Causal Inference (<em>JCI</em>) is a fully peer-reviewed, open access, electronic-only journal.</p> <p style="color: #3c3c3c;">JCI publishes papers on theoretical and applied causal research across the range of academic disciplines that use quantitative tools to study causality.</p> <p style="color: #3c3c3c;">The past two decades have seen causal inference emerge as a unified field with a solid theoretical foundation, useful in many of the empirical and behavioral sciences. <em>Journal of Causal Inference</em> aims to provide a common venue for researchers working on causal inference in biostatistics and epidemiology, economics, political science and public policy, cognitive science and formal logic, and any field that aims to understand causality. The journal serves as a forum for this growing community to develop a shared language and study the commonalities and distinct strengths of their various disciplines' methods for causal analysis.</p> <p style="color: #3c3c3c;">Existing discipline-specific journals tend to bury causal analysis in the language and methods of traditional statistical methodologies, creating the inaccurate impression that causal questions can be handled by routine methods of regression or simultaneous equations, glossing over the special precautions demanded by causal analysis. In contrast, <em>JCI</em> highlights both the uniqueness and interdisciplinary nature of causal research.</p> <p><strong style="color: #2a2a2a;">Topics<br /></strong><span style="color: #2a2a2a;">Any field aiming at understanding causality, especially</span></p> <ul style="color: #2a2a2a;"> <ul style="color: #2a2a2a;"> <li>Biostatistics and epidemiology</li> <li>Economics</li> <li>Political science</li> <li>Public policy</li> <li>Cognitive science</li> <li>Formal logic</li> </ul> </ul> <p style="color: #3c3c3c;"> </p> <p><span style="color: #2a2a2a;">Causal inference:</span></p> <ul style="color: #2a2a2a;"> <li>Research design</li> <li>Causal model and target parameter specification</li> <li>Identifiability</li> <li>Statistical estimation</li> <li>Sensitivity analysis/interpretation.</li> <li>Quantitative statistics’ elaboration of causal methods in applied data analyses</li> <li>Cross-disciplinary methodological research</li> <li>History of the causal inference field and its philosophical underpinnings</li> </ul> <p style="color: #3c3c3c;"><strong>Article formats<br /></strong>Original research articles, book reviews, short communications on topics that aim to stimulate public debate and bring unorthodox perspectives to open questions</p>, totalCites=578, brief=J CAUSAL INFERENCE杂志暂不明确行业，暂不明确子行业的级别不明杂志, articleType=本刊接收类型不明, medsciHeat=黑红, medsciComment=J CAUSAL INFERENCE在该细分领域可能是一流杂志，可能是创刊时间短或不是热门学科，整体来说，国内学者关注度仍然不够。对于投稿而言，建议多向"&abbr&"投稿，当然期刊也应该加强品牌宣传。, medsciExplanation=MedSci期刊指数是根据中国科研工作者（含医学临床，基础，生物，化学等学科）对SCI杂志的认知度，熟悉程度，以及投稿的量等众多指标综合评定而成。当然，具体的，您还可以结合“<a href='https://www.medsci.cn/sci/submit.do?id=bfe116607'>投稿经验系统</a>”，进行综合判断，这更是大家的实战经验，值得分享和参考。<br> 注意，上述MedSci期刊指数采用MedSci专利技术，由计算机系统自动计算，并给出建议，存在不准确的可能，仅供您投稿选择杂志时参考。, tags=null, citeScoreList=[GetImpactFactorCiteScoreListResponse(year=2020, citescore=2.0), GetImpactFactorCiteScoreListResponse(year=2023, citescore=1.9)], medsciIndexList=[GetImpactFactorMedsciIndexListResponse(year=2020, medsciHotlight=0.302), GetImpactFactorMedsciIndexListResponse(year=2021, medsciHotlight=0.45), GetImpactFactorMedsciIndexListResponse(year=2022, medsciHotlight=0.428), GetImpactFactorMedsciIndexListResponse(year=2023, medsciHotlight=0.602), GetImpactFactorMedsciIndexListResponse(year=2024, medsciHotlight=0.983)], citeScoreGradeList=[], totalJcrAreaList=[], pmcUrl=https://www.ncbi.nlm.nih.gov/nlmcatalog?term=2193-3677[ISSN], pubmedUrl=https://www.ncbi.nlm.nih.gov/pubmed?cmd=search&term=Journal of Causal Inference[ta], article_number=7, article_number_cn=null, earlyWarning=null, linkOutUrl=null, isJournalMember=false, unscrambleContent=null, dayViewCount=false, endexampletyle=暂无数据)