thedixitjain Cognitive Psychology Workflow Router (cogpsych-workflow)
The orchestrator for a Cognitive Psychology (Elsevier) submission. The journal's two defining features are that it rewards longer, integrative, model-driven papers — typically a multi-experiment program tied to a formal/computational model — and that it expects data, model code, and analysis scripts to be shareable. The router makes sure the contribution is theory-and-model-shaped from the start, then sends the user to the matching skill.
When to trigger
- Starting a new Cognitive Psychology paper and unsure where to begin
- Mid-project and unsure which skill applies next
- Choosing the contribution type (empirical-only vs. experiment-plus-model vs. modeling-led)
- Returning with a decision letter (route to
cogpsych-rebuttal)
First question: contribution type
| Situation | Type | Route note |
|---|---|---|
| Several controlled experiments that jointly constrain a theory | Multi-experiment empirical | main pipeline; make each experiment add inference, not repeat |
| Experiments plus a fitted formal model (the common shape here) | Experiment + model | pull cogpsych-theory-and-hypotheses (formalize) + cogpsych-data-analysis (fit/compare) forward |
| A new model / analysis tested against existing or new data | Modeling-led | cogpsych-theory-and-hypotheses → cogpsych-data-analysis (model recovery + comparison) |
| Integrative theoretical synthesis or review with a substantive advance | Theoretical / review | cogpsych-literature-positioning + cogpsych-theory-and-hypotheses |
A single short experiment reporting one effect is usually the wrong shape for this venue — that is a Psychological Science / short-report contribution. Cognitive Psychology wants the longer arc.
Routing map (stage → skill)
Idea / fit? → cogpsych-topic-selection
Theory + model + predictions? → cogpsych-theory-and-hypotheses
Where does it sit in the field? → cogpsych-literature-positioning
Experiments / stimuli / power? → cogpsych-study-design
Analysis + model fit/comparison? → cogpsych-data-analysis
Exhibits (data + model fit)? → cogpsych-tables-figures
Long-form prose clear? → cogpsych-writing-style
Data + model code + materials open? → cogpsych-open-science-and-transparency
How will it be judged? → cogpsych-review-process
Ready to submit (Editorial Manager)? → cogpsych-submission
Got an R&R / decision? → cogpsych-rebuttal
Default order
topic-selection → theory-and-hypotheses → literature-positioning → study-design → data-analysis → tables-figures → writing-style → open-science-and-transparency → review-process → submission → rebuttal
Theory comes before positioning here on purpose: the formal model is the contribution, so
formalize the account first, then position it against rival models. For experiment-plus-model papers,
the model is co-designed with the experiments — iterate theory-and-hypotheses ↔ study-design.
Worked micro-example — routing a live project (illustrative)
A team has three preregistered recognition-memory experiments and a competing pair of models (unequal-variance signal detection vs. a dual-process account) they want to fit and compare.
Type: Experiment + model (multi-experiment program, model comparison).
Entry: not idea-stage → skip topic-selection; they are at theory/design/analysis.
Route: theory-and-hypotheses (formalize both models + the predictions that
separate them)
→ study-design (stimuli, list construction, power for the critical
contrast across all three experiments)
→ data-analysis (fit both models; compare with AIC/BIC + Bayes
factors; report parameter recovery)
→ tables-figures (overlay model fit on data, not bars of means)
→ writing-style (integrate three experiments into one argument)
→ open-science-and-transparency (deposit data + model code + scripts)
→ submission (Editorial Manager) ; on R&R → rebuttal.
Flag: the model comparison must be pre-committed where possible and the
fits reproducible from the deposited code.
Stage-triage table (symptom → skill)
| What the author says | Stage | Route to |
|---|---|---|
| "Is one experiment enough for this journal?" | fit | cogpsych-topic-selection |
| "I have data but no formal model" | theory | cogpsych-theory-and-hypotheses |
| "Which model is better, AIC or BIC?" | analysis | cogpsych-data-analysis |
| "Reviewer says my experiments don't constrain the theory" | design | cogpsych-study-design |
| "How do I show model fit, not just means?" | exhibits | cogpsych-tables-figures |
| "Reviewer can't run my model code" | transparency | cogpsych-open-science-and-transparency |
| "I have an R&R" | revision | cogpsych-rebuttal |
Routing pitfalls specific to this venue
- Sending an experiment-only project straight to
cogpsych-submissionwithout a formal model or an integrative theoretical payoff — the journal's identity is model-driven theory development. - Treating the model as an afterthought bolted on at the end, instead of co-designing experiments to
discriminate models from the start (iterate
theory-and-hypotheses↔study-design). - Deferring
cogpsych-open-science-and-transparency: model code and fits should be reproducible from deposit, not promised at acceptance.
Anti-patterns
- Pitching a single-experiment, single-effect paper (wrong length/ambition for this venue)
- Reporting experiments with no formal model and no integrative theoretical advance
- A model that is described in prose but never fit to data or compared to a rival
- Leaving data/model code/scripts unshareable until acceptance
Output format
【Stage】idea / theory / positioning / design / analysis / exhibits / writing / transparency / review / submit / rebut
【Type】Multi-experiment empirical / Experiment + model / Modeling-led / Theoretical-review
【Route to】cogpsych-<skill>
【Why】one line
【Then】the next skill after that
Supplementary resources
../../resources/external_tools.md— modeling, model-comparison, mixed-model and preregistration tooling../../resources/official-source-map.md— official Cognitive Psychology / Elsevier URLs behind every fact in this pack
Source: brycewang-stanford/Awesome-Journal-Skills → Cognitive-Psychology-Skills/skills/cogpsych-workflow/SKILL.md