{"id":12934,"date":"2026-10-26T14:21:08","date_gmt":"2026-10-26T18:21:08","guid":{"rendered":"https:\/\/shaire.ca\/?p=12934"},"modified":"2026-11-06T10:23:52","modified_gmt":"2026-11-06T15:23:52","slug":"advances-in-causal-inference-methods-applied-to-real-world-evidence-part-2","status":"publish","type":"post","link":"https:\/\/shaire.ca\/en\/advances-in-causal-inference-methods-applied-to-real-world-evidence-part-2\/","title":{"rendered":"Advances in causal inference methods applied to real-world evidence (Part 2)"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"12934\" class=\"elementor elementor-12934\" data-elementor-post-type=\"post\">\n\t\t\t\t<div class=\"elementor-element elementor-element-bf11ca8 e-con-full e-flex e-con e-parent\" data-id=\"bf11ca8\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ebd118b elementor-widget elementor-widget-heading\" data-id=\"ebd118b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h5 class=\"elementor-heading-title elementor-size-default\">When: November 3rd, 2026 from 3:00-4:30 PM ET <\/h5>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4812d8f elementor-widget elementor-widget-text-editor\" data-id=\"4812d8f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p style=\"font-weight: 400;\">This webinar will introduce clinicians and researchers to the foundations of <strong>exchangeability and causal inference methods for measured confounding<\/strong>. This session revisits the exchangeability assumption in the context of respiratory health research and introduces two classical approaches for restoring exchangeability when confounders are measured: inverse probability of treatment weighting (IPTW) and g-computation. The first half covers the theory behind each method, including how propensity scores are constructed and how standardization works. The second half is a hands-on practical session in R, where participants apply these methods to a worked example. Prior experience with R is encouraged but not required.<\/p><p style=\"font-weight: 400;\"><strong>Participants will receive installation instructions and a list of required R packages one week before the session.<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5201268 elementor-widget elementor-widget-button\" data-id=\"5201268\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/events.teams.microsoft.com\/event\/268fa1a8-d122-4a78-868c-2394a6ef3510@60b81999-0b7f-412d-92a3-e17d8ae9e3e0?source=copyLinkLegacyShareEventDialog\" target=\"_blank\" rel=\"noopener noreferrer nofollow\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Register here<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ffd2388 elementor-widget elementor-widget-spacer\" data-id=\"ffd2388\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-23ad3fb elementor-widget elementor-widget-heading\" data-id=\"23ad3fb\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Speakers<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-61d1e04 e-con-full e-flex e-con e-child\" data-id=\"61d1e04\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-59143c8 elementor-widget elementor-widget-image\" data-id=\"59143c8\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/shaire.ca\/wp-content\/uploads\/elementor\/thumbs\/Cristina_Longo-rt5lc5o322eukcg0bt9mc3hdzx58pukw7hel1b0hre.jpg\" title=\"Cristina Longo\" alt=\"Dr. Cristina Longo\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-11e67a9 elementor-widget elementor-widget-text-editor\" data-id=\"11e67a9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h3>Dr. Cristina Longo<\/h3><p class=\"profile-title\">Assistant Professor at Universit\u00e9 de Montreal<\/p><p class=\"profile-bio\">Cristina is a pediatric epidemiologist with expertise in pharmacoepidemiology, causal inference, and machine learning.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-781c269 e-con-full e-flex e-con e-child\" data-id=\"781c269\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ae80ca1 elementor-widget elementor-widget-image\" data-id=\"ae80ca1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/shaire.ca\/wp-content\/uploads\/elementor\/thumbs\/Albina_tskhay-rti1wfj6vs6k4o6bqzr9g4wbr4cwlo3x20ojzft1pm.jpg\" title=\"Albina_tskhay\" alt=\"Dr. Albina Tskhay\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0b8ac67 elementor-widget elementor-widget-text-editor\" data-id=\"0b8ac67\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h3>Dr. Albina Tskhay<\/h3><p class=\"profile-title\">Postdoctoral Researcher at The Digital Health and Network Multi-Omic Laboratory<\/p><p class=\"profile-bio\">\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-843c1ce e-flex e-con-boxed e-con e-parent\" data-id=\"843c1ce\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1a44398 elementor-widget elementor-widget-spacer\" data-id=\"1a44398\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Introduces causal inference methods for measured confounding, covering IPTW, g-computation, and their practical application in R.<\/p>\n","protected":false},"author":7,"featured_media":12626,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"iawp_total_views":11,"footnotes":""},"categories":[48],"tags":[39],"class_list":["post-12934","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-webinar-resources","tag-past"],"acf":[],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.5 - aioseo.com -->\n\t<meta name=\"description\" content=\"Introduces causal inference methods for measured confounding, covering IPTW, g-computation, and their practical application in R.\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"rachelle Aucoin\"\/>\n\t<link rel=\"canonical\" href=\"https:\/\/shaire.ca\/en\/advances-in-causal-inference-methods-applied-to-real-world-evidence-part-2\/\" \/>\n\t\t<meta name=\"generator\" content=\"All in One SEO 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