Design quasi-experimental studies with causal rigor.
Move from research idea to structured synopsis in guided steps: design type prediction, assignment strategy, identification strategy, comparison group definition, and analysis planning in one connected workflow.
Best-fit quasi-experimental design selected with alternatives.
Non-random assignment mechanism documented.
Causal identification logic prepared for review.
Eleven connected steps from idea to draft synopsis.
Each step builds on the last. Complete all eleven for a review-ready quasi-experimental protocol.
Design prediction
Match your idea to the optimal type from 17 quasi-experimental designs with alternatives for review.
Research question
Craft a causal question acknowledging non-random assignment and specifying the counterfactual.
Assignment strategy
Document the non-random assignment mechanism, selection process, and known determinants.
Hypothesis & variables
Specify the treatment effect hypothesis, primary outcome, and potential confounders.
Theory mapping
Connect the intervention to a program theory or policy logic model for coherence.
Comparison group design
Comparison unit selection rationale, baseline equivalence testing plan, and common trend assumptions.
Identification strategy
Design-specific causal identification logic: DiD parallel trends, RD continuity, IV exclusion restriction, or ITS counterfactual.
Sample size logic
Power calculation with minimum detectable effect, intraclass correlation, and clustering adjustments.
Measurement plan
Outcome and covariate measurement timing, data source operationalization, and attrition management.
Analysis plan
Primary model specification, covariate adjustment, sensitivity and robustness checks.
Synopsis output
Reviewable draft in three detail tiers — standard, academic, journal-ready.
See what the protocol draft looks like.
This is a preview of what the workflow produces. Every section is editable before expert sign-off.
Study objective
Estimate the effect of a school-based nutrition program on BMI-for-age z-score and overweight prevalence among adolescents aged 11–15, using a non-equivalent control group design with propensity score adjustment.
Assignment strategy
Schools self-selected into the program based on principal initiative and district funding availability. Assignment mechanism is non-random and driven by leadership motivation and resource access. Known determinants: school size, urban/rural classification, and prior health program participation.
Identification strategy
Non-equivalent control group with difference-in-differences estimation. Parallel pre-intervention trend assumption tested across 3 pre-program measurement waves. Baseline equivalence assessed using standardized mean differences; propensity score weighting applied if SMD >0.1 on any covariate.
Generic AI output
- Unstructured with mixed assumptions
- No clear step progression
- Harder for teams to review and revise
- Confidence without boundaries
QuasiMinds workflow
- Connected sequence from idea to synopsis
- Assignment and identification strategy steps unique to quasi-experimental design
- Causal identification logic documented at each step
- TREND 2004-oriented output with transparent logic
What researchers ask before they start.
What quasi-experimental designs does QuasiMinds support?
QuasiMinds covers 17 types including non-equivalent control group, difference-in-differences, regression discontinuity (sharp and fuzzy), interrupted time series, instrumental variables, propensity score matching, pre-post without control, and stepped-wedge non-randomized designs.
What is the Identification Strategy step?
Step 7 is unique to quasi-experimental design. It documents the causal identification logic specific to your design — the parallel trends assumption for DiD, continuity assumption for RD, exclusion restriction for IV, or counterfactual construction for ITS. This is the core of causal credibility.
What does “TREND 2004-oriented” mean?
TREND (Transparent Reporting of Evaluations with Nonrandomized Designs) is the 22-item reporting standard for quasi-experimental studies. QuasiMinds structures synopsis output to align with TREND items for transparent, replicable reporting.
What’s included free?
Design prediction (Step 1) is free with login — identify the best quasi-experimental design for your study. All TREND 2004 checklists and identification strategy guides are also free for members.
Start with design prediction. Stay for the full workflow.
Identify your optimal quasi-experimental design for free. Unlock the complete 11-step protocol workflow with Scholar Pro.
“The quality of your research can never exceed the clarity of your method.” — Rajesh S.K., Founder