From cognitive-psychology-skills
Structures formal/computational models for Cognitive Psychology manuscripts. Derives discriminating predictions that separate your account from rival models to avoid 'just a curve fit' objections.
How this skill is triggered — by the user, by Claude, or both
Slash command
/cognitive-psychology-skills:cogpsych-theory-and-hypothesesThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Cognitive Psychology rewards a **formal account of a cognitive process** — a computational or
Cognitive Psychology rewards a formal account of a cognitive process — a computational or mathematical model whose parameters have interpretable meaning and whose predictions can be fit to data and compared against rival models. The cardinal move here is to turn a verbal theory into a model that makes the experiments discriminating, and to separate predicted (confirmatory) from discovered (exploratory) results.
cogpsych-study-design)cogpsych-data-analysis).A recognition-memory program adjudicating two models, written so prediction status is legible.
Theory: Recognition reflects a single continuous memory-strength signal;
the unequal-variance signal-detection (UVSD) model formalizes it.
Rival: A dual-process account adds a threshold recollection process (DPSD).
Formalization:
UVSD parameters: d', sigma(old). DPSD parameters: R (recollection),
d' (familiarity). Both fit the same confidence-ROC data.
Discriminating prediction (confirmatory, preregistered, Exps 1-3):
The z-ROC slope is < 1 and *linear* under UVSD; DPSD predicts a
characteristic U-shaped/curved z-ROC. The shape, not the fit index,
separates them.
Exploratory: any post hoc parameter that improves DPSD fit is reported as
exploratory, not as a prediction.
Disconfirming: a reliably curved z-ROC across experiments counts against UVSD,
stated up front.
| Reviewer pushback | Cognitive Psychology fix |
|---|---|
| "Atheoretical / mechanism unclear" | state the mechanism in words, then give the formal model before the experiments |
| "The model is just a curve fit" | show a falsifiable, identifiable model with a crossed qualitative prediction, not only a fit edge |
| "Your data can't distinguish the accounts" | design the discriminating signature into the experiments; formalize both rivals in the same language |
| "Parameters are uninterpretable" | give each free parameter a psychological meaning and a recovery check |
| "This looks post hoc" | mark confirmatory vs. exploratory; pre-commit the model comparison where feasible |
cogpsych-data-analysis).【Theory】the mechanism/representation, briefly
【Model】formalization: parameters + their psychological meaning
【Rival(s)】competing account(s) in matched formal language
【Discriminating prediction】the signature that separates the models
【Status】confirmatory (pre-committed) vs exploratory
【Disconfirming evidence】what would count against the model
【Next】cogpsych-literature-positioning
../../resources/external_tools.md — modeling frameworks, model-recovery and preregistration tools../../resources/official-source-map.md — scope and modeling emphasisnpx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin cognitive-psychology-skillsDerives predictions from a Psychological Review theory and confronts them with existing data and rival models, serving as the journal's substitute for an empirical results section.
Positions a Cognitive Psychology manuscript against rival models and prior empirical programs by framing the theoretical question and showing why existing evidence cannot settle it.
Guides writing the theory and hypotheses section for Psychological Science manuscripts, ensuring clear separation of confirmatory (preregistered) vs exploratory analyses and preventing HARKing.