JMR enforces statistics reporting more explicitly than generic top journals. Empirical papers must report:
AMA results-reporting style: no leading zero before the decimal (write .97, p = .032), and no more than three decimal places. Apply this to every table and in-text statistic.
| Design / claim | Estimator |
|---|---|
| Experiment (factorial, between/within) | ANOVA / regression; estimated marginal means; planned contrasts |
| Behavioral mediation | Bootstrapped indirect effects (e.g., PROCESS), bias-corrected CIs |
| Moderation / moderated mediation | Interaction term + simple slopes; conditional indirect effects |
| Panel / observational causal | FE / DiD (modern staggered estimators); cluster-robust SE |
| Endogenous regressor | IV/2SLS, control function; report first stage and instrument tests |
| Discrete choice / demand | Logit/probit; random-coefficient (BLP-style) demand |
| Heterogeneity | Hierarchical Bayes / mixture models |
| Counts / limited DV | Poisson/NB, Tobit, as the outcome requires |
Cluster standard errors to the sampling/assignment structure (e.g., by participant, store, or market).
For each table or study, write one ledger row before drafting results:
| Result | Claim it supports | Required statistic | Practical meaning |
|---|---|---|---|
| Main treatment or model estimate | What marketing decision, mechanism, or theory point changes? | Exact p-value, standard error, CI/effect size | Unit change, percentage lift, WTP/profit/customer impact |
| Mediation/process result | Which mechanism is supported and which rival is weaker? | Indirect effect with CI; moderation where relevant | Why the process matters for managers or theory |
| Robustness / alternative model | Which threat is reduced? | Same reporting discipline as main result | Whether conclusion changes in magnitude or direction |
| Counterfactual / simulation | What marketplace decision follows? | Parameter uncertainty and sensitivity | Managerial action implied by the estimate |
If the practical-meaning column is empty, the result is not ready for a JMR results paragraph. JMR reviewers expect precision, but they also expect a marketing payoff.
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. JMR mixes experiments, structural models, and quasi-experiments; the chain below serves the experimental and reduced-form lanes, while structural demand estimation uses its own toolkit.
romano_wolf (step-down FWER) or
benjamini_hochberg — report the adjusted threshold.oster_delta / sensemakr.wild_cluster_bootstrap (few clusters), twoway_cluster / conley;
multilevel data → cluster at the right level.audit_result(result_id) lists the missing checks and the
exact suggest_function for each.etable / did_summary_to_latex from the handle — no retyped numbers.Keep the decisive checks in the body and the exhaustive battery in the appendix. See the executed chain in the JF execution walkthrough.
[Target] JMR
[Genre] behavioral / modeling-econometric
[Estimator] matches design? SE clustering ...
[Exact stats] p three-digit / SEs / effect sizes: pass/fix
[AMA number style] no leading zero, <= 3 decimals: pass/fix
[Identification or process] diagnostics reported
[Result-to-claim ledger] claim + practical meaning complete
[Replication] Web Appendix + code/materials ready
[Next skill] jmr-contribution-framing