QuasiMinds · Quasi-Experimental Design — a specialized subdomain of RSMinds
Design Quasi-Experimental Studies
From Idea to TREND Synopsis
Difference-in-differences, regression discontinuity, instrumental variables, propensity-score and interrupted time series designs. 13-step workflow with dedicated Assignment and Identification strategy steps — AI proposes the design, you document the causal identification logic before you commit. Built on TREND 2004.
quasi-experimental subtypes across 6 categories
workflow sections — idea to TREND synopsis
TREND 2004 reporting items mapped to sections
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How QuasiMinds works
The 13-section workflow
Each section is its own AI-assisted accordion. Outputs flow forward — your PICO informs the assignment mechanism; assignment informs identification; identification threads through analysis; everything assembles into a TREND synopsis.
Idea & Design Subtype
Inputs
AI action
Output
Best-fit subtype across 17 quasi-experimental designs with alternatives + category (DiD / RDD / PSM / IV / ITS / Hybrid).
PICO Framework
Inputs
AI action
Output
Population / Intervention / Comparison / Outcome — with the counterfactual comparison group made explicit.
Research Question & FINER
Inputs
AI action
Output
3 causal question drafts acknowledging non-random assignment + FINER scoring.
Hypothesis & Variables
Inputs
AI action
Output
Treatment-effect H1 / H0 + variables: predictor, outcome, confounders, mediators, moderators.
Theory & Framework
Inputs
AI action
Output
3 theory / program-logic candidates with citations + conceptual framework.
Population & Eligibility
Inputs
AI action
Output
Treatment + comparison unit selection, inclusion / exclusion criteria, baseline-equivalence plan.
Sample Size & Power
Inputs
AI action
Output
N with minimum detectable effect, design effect, and design-specific adjustments (RDD bandwidth, PSM matched pairs).
Assignment & Control Strategy
Inputs
AI action
Output
The non-random assignment mechanism, group formation, matching / cutoff / instrument specification, placebo tests.
Identification Strategy & Threats
Inputs
AI action
Output
Design-specific causal identification: DiD parallel trends, RD continuity, IV exclusion restriction, or ITS counterfactual — with test plan + robustness.
Intervention / Exposure Protocol
Inputs
AI action
Output
TIDieR-structured protocol — whether the intervention is a policy, exposure, or naturally occurring event — with comparator and fidelity plan.
Analysis Plan
Inputs
AI action
Output
Primary model specification (DiD interaction, RD LATE, IV/2SLS, ITS segmented), sensitivity and robustness checks.
TREND Compliance
Inputs
AI action
Output
TREND 2004 22-item checklist scored against your protocol, with deviations documented.
Synopsis / Protocol
Inputs
AI action
Output
TREND-compliant synopsis exportable as DOCX, PDF, or Markdown.
Subtype coverage
17 quasi-experimental subtypes — all covered
From difference-in-differences and regression discontinuity to instrumental variables, propensity-score methods, and interrupted time series. Every subtype gets its own identification logic, design-specific notation, and sample-size formulas.
Difference-in-Differences
3 designsStandard DiD
Two groups, two periods — parallel-trends identification.
Staggered DiD
Treatment adopted at different times across units.
Synthetic Control DiD
Weighted donor pool builds the counterfactual.
Regression Discontinuity
3 designsSharp RDD
Deterministic cutoff — treatment fully determined by threshold.
Fuzzy RDD
Probabilistic cutoff — instrument for actual receipt.
Geographic / Spatial RDD
Boundary as the running-variable cutoff.
Propensity Score Methods
3 designsPSM Matching
Match treated to controls on the propensity score.
PSM Weighting (IPTW)
Inverse-probability-of-treatment weighting.
PSM Stratification
Stratify on propensity-score quantiles.
Instrumental Variables
2 designsStandard IV / 2SLS
Two-stage least squares with an exogenous instrument.
Mendelian Randomization
Genetic variants as instruments for exposure.
Interrupted Time Series
3 designsStandard ITS
Segmented regression around an interruption point.
Controlled ITS (CITS)
Adds a comparison series for the counterfactual.
Multiple-Baseline ITS
Staggered interruptions across multiple series.
Hybrid Designs
3 designsDiD + PSM
Weight or match, then difference-in-differences.
RDD + IV
Fuzzy discontinuity used as the instrument.
ITS + DiD
Time-series interruption with a control series.
Compliance
Built on the quasi-experimental
standards reviewers expect
Your protocol is scored against the TREND 2004 checklist in real time.
Why this matters
Causal claims,
backed by an explicit identification strategy
Other tools
Run the regression. Claim causation.
Without random assignment, a coefficient is only causal if an identifying assumption holds — parallel trends for DiD, continuity at the cutoff for RD, the exclusion restriction for IV. Skip that step and a reviewer will ask why you never tested it, and your “effect” may be selection in disguise.
QuasiMinds
A dedicated identification-strategy step.
Step 9 documents the design-specific assumption, why it is plausible, how you will test it, and what you will do if it is violated — before you lock the analysis plan. The assumption is matched to the subtype automatically.
- Assumption matched to the design — parallel trends, continuity, exclusion, or counterfactual.
- Explicit test plan + sensitivity / robustness checks.
- Placebo and pre-trend tests prompted where the design demands them.
Identifying assumption
Parallel trends
treated & control move together absent treatment
Test plan
event-study, 3 pre-periods
pre-trend coefficients ≈ 0
If violated
synthetic control
fallback identification documented
Plans
Simple pricing
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- All 17 quasi-experimental subtypes
- 13-section workflow
- TREND + TIDieR exports
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FAQ
Frequently asked questions
Common questions from evaluators, supervisors, and IEC reviewers.
Which quasi-experimental designs does QuasiMinds cover?
All 17 mainstream subtypes across 6 categories — difference-in-differences (standard, staggered, synthetic-control); regression discontinuity (sharp, fuzzy, geographic); propensity-score methods (matching, IPTW weighting, stratification); instrumental variables (2SLS, Mendelian randomization); interrupted time series (standard, controlled, multiple-baseline); and three hybrid designs (DiD+PSM, RDD+IV, ITS+DiD).
What is the Identification Strategy step?
Step 9 is unique to quasi-experimental design. It documents the causal identification logic specific to your design — the parallel-trends assumption for DiD, continuity at the cutoff for RD, the exclusion restriction for IV, or the counterfactual for ITS — with a test plan and a fallback if the assumption is violated. This is the core of causal credibility without randomization.
How does the Assignment Strategy step work?
Step 8 documents the non-random assignment mechanism: how units came to be treated vs control, the selection process, known determinants, and (where relevant) matching variables, cutoff thresholds, or instruments. It replaces the randomization step you would find in an RCT tool.
What does "TREND 2004-oriented" mean?
TREND (Transparent Reporting of Evaluations with Nonrandomized Designs) is the 22-item reporting standard for quasi-experimental and other non-randomized evaluations. QuasiMinds maps each TREND item to a workflow section and scores your protocol against the checklist in real time.
How does PICO apply when there is no randomization?
QuasiMinds uses PICO (Population / Intervention / Comparison / Outcome) but makes the comparison group — the counterfactual — explicit, since you observe rather than assign treatment. The intervention may be a policy, an exposure, or a naturally occurring event.
Does the sample-size calculator handle design-specific needs?
Yes — minimum detectable effect, intraclass correlation, and clustering adjustments, plus design-specific parameters: RDD bandwidth, PSM matched pairs, IV first-stage strength, and ITS time points. The calculator adapts to the subtype you selected.
Can I import an existing protocol?
Yes. Paste any synopsis or PICO statement and the tool extracts population, intervention, comparison, and outcome so you continue from where you left off.
What export formats are supported?
DOCX, PDF, and Markdown in APA 7, Academic, or Institutional styles — with a title page, table of contents, numbered sections, and an Appendix A study-parameters table (PICO, variables, assignment method, identification assumption, sample size). The TREND compliance score appears in the document subtitle.
Is there a free way to try it?
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.
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