[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-31359":3,"doc-seo-31359":27},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"file_id":15,"file_url":16,"file_type":17,"file_size":18,"view_count":4,"is_deleted":4,"is_public":19,"is_downloadable":19,"audit_status":19,"page_count":20,"language":21,"language_code":22,"table_of_contents":23,"faqs":24,"seo_title":13,"seo_description":14,"update_tm":25,"read_time":26},31359,1099513958762,"Logic","https://ap-avatar.wpscdn.com/avatar/1000023916a998db790?_k=1776737595927829259",8,"Research & Report","Inverse Odds Ratio-Weighted Estimation for Causal Mediation Analysis","A causal mediation analysis framework aims to quantify how a point exposure affects an outcome directly versus indirectly through an intermediate mediator on the causal pathway. This paper introduces an inverse odds ratio-weighted estimator of natural direct and indirect effects. The method weights observations by the inverse of an estimated odds ratio function linking exposure and mediator, supports effect decomposition across many regression models, and accommodates generalized linear models and Cox proportional hazards. It is implementable in standard software with observation-specific weights and extends naturally to multiple mediators of diverse types.","cbCaifvq6iOzBk99","https://ap.wps.com/l/cbCaifvq6iOzBk99","pdf",196055,1,14,"English","en","# Introduction\n## Causal mediation goals and definitions\n## Natural direct and indirect effects vs controlled direct effects\n## Identification assumptions\n# Method overview\n## Inverse odds ratio-weighted estimator\n## Effect decomposition across regression models\n## Multiple mediators and implementation","[{\"question\":\"What does natural direct and indirect effects mean in causal mediation analysis?\",\"answer\":\"Natural direct effect captures the exposure effect when the mediator is set to the level it would take without exposure, while natural indirect effect captures the part transmitted through the mediator. Together they sum to the total exposure effect.\"},{\"question\":\"How does the inverse odds ratio-weighted approach estimate natural direct and indirect effects?\",\"answer\":\"It assigns each observation a weight equal to the inverse of an estimated odds ratio function relating exposure to the mediator. These weighted components are then used to decompose total effects into direct and indirect parts.\"},{\"question\":\"Which models can the proposed method be applied to?\",\"answer\":\"The approach can be used for generalized linear models with nonlinear link functions and also for survival outcomes using Cox proportional hazards regression, as long as appropriate observation-level weights are available.\"}]",1779397221,35,{"code":4,"msg":28,"data":29},"ok",{"site_id":30,"language":22,"slug":31,"title":13,"keywords":32,"description":14,"schema_data":33,"social_meta":84,"head_meta":86,"extra_data":88,"updated_unix":25},105,"inverse-odds-ratio-weighted-estimation-for-causal-mediation-analysis","",{"@graph":34,"@context":83},[35,52,66],{"@type":36,"itemListElement":37},"BreadcrumbList",[38,42,46,49],{"item":39,"name":40,"@type":41,"position":19},"https://docshare.wps.com","Home","ListItem",{"item":43,"name":44,"@type":41,"position":45},"https://docshare.wps.com/document/","Document",2,{"item":47,"name":12,"@type":41,"position":48},"https://docshare.wps.com/document/research-report/",3,{"item":50,"name":13,"@type":41,"position":51},"https://docshare.wps.com/document/inverse-odds-ratio-weighted-estimation-for-causal-mediation-analysis/31359/",4,{"url":50,"name":13,"@type":53,"author":54,"headline":13,"publisher":56,"fileFormat":59,"description":14,"dateModified":60,"datePublished":60,"encodingFormat":59,"isAccessibleForFree":61,"interactionStatistic":62},"DigitalDocument",{"name":9,"@type":55},"Person",{"url":39,"name":57,"@type":58},"DocShare","Organization","application/pdf","2026-05-21",true,{"@type":63,"interactionType":64,"userInteractionCount":4},"InteractionCounter",{"@type":65},"ViewAction",{"@type":67,"mainEntity":68},"FAQPage",[69,75,79],{"name":70,"@type":71,"acceptedAnswer":72},"What does natural direct and indirect effects mean in causal mediation analysis?","Question",{"text":73,"@type":74},"Natural direct effect captures the exposure effect when the mediator is set to the level it would take without exposure, while natural indirect effect captures the part transmitted through the mediator. Together they sum to the total exposure effect.","Answer",{"name":76,"@type":71,"acceptedAnswer":77},"How does the inverse odds ratio-weighted approach estimate natural direct and indirect effects?",{"text":78,"@type":74},"It assigns each observation a weight equal to the inverse of an estimated odds ratio function relating exposure to the mediator. These weighted components are then used to decompose total effects into direct and indirect parts.",{"name":80,"@type":71,"acceptedAnswer":81},"Which models can the proposed method be applied to?",{"text":82,"@type":74},"The approach can be used for generalized linear models with nonlinear link functions and also for survival outcomes using Cox proportional hazards regression, as long as appropriate observation-level weights are available.","https://schema.org",{"og:url":50,"og:type":85,"og:title":13,"og:site_name":57,"og:description":14},"article",{"robots":87,"canonical":50},"index,follow",{"doc_id":7,"site_id":30}]