PLanet: Formalizing and Analyzing Assignment Procedures in the Design of Experiments
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2025
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866914470279774208 |
|---|---|
| author | Bielicke, London Zhang, Anna Tyagi, Shruti Berger, Emery Chlipala, Adam Jun, Eunice |
| author_facet | Bielicke, London Zhang, Anna Tyagi, Shruti Berger, Emery Chlipala, Adam Jun, Eunice |
| contents | Experimental designs reflect assumptions about variable relationships that determine what causal queries researchers can answer through the experiment. Accounting for and communicating these assumptions is essential for drawing valid, generalizable conclusions from scientific experiments. Unfortunately, existing experimental design tools elide these details, expecting researchers to reason about design decisions and assumptions on their own. To surface assumptions and enable design exploration, we introduce a grammar of composable operators for constructing experimental assignment procedures grounded in matrix algebra. The PLanet DSL implements this grammar and compiles PLanet programs into constraint satisfaction problems over matrices. Together, PLanet's composable grammar and matrix representation enable a static analysis to determine which causal queries are testable under different assumptions. In an expressivity evaluation, PLanet was the most expressive of existing DSLs. Critical reflections with the authors of these DSLs revealed that PLanet makes design choices explicit without requiring procedural specification. Think-aloud studies showed that PLanet facilitated design exploration and surfaced assumptions researchers may otherwise overlook. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_09094 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PLanet: Formalizing and Analyzing Assignment Procedures in the Design of Experiments Bielicke, London Zhang, Anna Tyagi, Shruti Berger, Emery Chlipala, Adam Jun, Eunice Human-Computer Interaction Experimental designs reflect assumptions about variable relationships that determine what causal queries researchers can answer through the experiment. Accounting for and communicating these assumptions is essential for drawing valid, generalizable conclusions from scientific experiments. Unfortunately, existing experimental design tools elide these details, expecting researchers to reason about design decisions and assumptions on their own. To surface assumptions and enable design exploration, we introduce a grammar of composable operators for constructing experimental assignment procedures grounded in matrix algebra. The PLanet DSL implements this grammar and compiles PLanet programs into constraint satisfaction problems over matrices. Together, PLanet's composable grammar and matrix representation enable a static analysis to determine which causal queries are testable under different assumptions. In an expressivity evaluation, PLanet was the most expressive of existing DSLs. Critical reflections with the authors of these DSLs revealed that PLanet makes design choices explicit without requiring procedural specification. Think-aloud studies showed that PLanet facilitated design exploration and surfaced assumptions researchers may otherwise overlook. |
| title | PLanet: Formalizing and Analyzing Assignment Procedures in the Design of Experiments |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2505.09094 |