2026-09-19T05:56:12Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/124696 2026-05-12 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Sundaram, Hari 2024-05 application/pdf en text Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-05-01 The student, Atharv Chandratre, accepted the attached license on 2024-04-23 at 17:07. The student, Atharv Chandratre, submitted this Thesis for approval on 2024-04-23 at 17:16. This Thesis was approved for publication on 2024-04-29 at 10:06. DSpace SAF Submission Ingestion Package generated from Vireo submission #20594 on 2024-09-16 at 00:50:20 DoViz: Intervention-centric interactive visualization for causal inference Chandratre, Atharv Shripad 2024-04-29 Causal Inference Interactive Visualization Data Visualization Tools Intervention Analysis Comparative Scenario Analysis User Interface Design Human-computer Interaction Causal Reasoning Visualization Software Causal inference is the process of understanding and quantifying cause-and-effect relationships from observed data. The process of causal inference often requires analysts to use visualizations for evaluating accuracy. However, existing visualization tools often lack the ability to communicate the effect of performing interventions on the data and comparatively visualizing their results. In this thesis, we address this gap using DoViz, an intervention-centric interactive visualization prototype. DoViz enables users to interact with independent variables, simulate explicit interventions, condition on confounders, and visualize the resultant causal effects. The user interface comprises an Intervention Panel for performing intuitive manipulations and an Inference Panel for visualizing intervention outcomes. A key feature of DoViz is its ability to perform comparative causal scenario analysis. Users can juxtapose multiple scenarios side-by-side, helping them draw more informed conclusions. The design process was driven by an iterative needfinding study, distilling a user-centric workflow around intervention, analysis, and comparison. Text eng https://hdl.handle.net/2142/124696 Copyright 2024 Atharv Chandratre M.S. Thesis Computer Science University of Illinois at Urbana-Champaign Computer Science