Stats
brycewang-stanford/Auto-Empirical-Research-Skills
Econometrics skill for descriptive statistics and summary tables.
A skill your agent uses when running and reporting the analysis for a Journal of the Academy of Marketing Science (JAMS) manuscript — selecting the estimator that matches the design (SEM/PLS, HLM…
Install Jams Data Analysis
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jams-data-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jams-data-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis .claude/skills/jams-data-analysis && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "jams-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis into .claude/skills/jams-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jams-data-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jams-data-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jams-data-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis .agents/skills/jams-data-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "jams-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis into .agents/skills/jams-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jams-data-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jams-data-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jams-data-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis .cursor/skills/jams-data-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "jams-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis into .cursor/skills/jams-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jams-data-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/brycewang-stanford/Awesome-Journal-Skills.git --path Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jams-data-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jams-data-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis .gemini/skills/jams-data-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "jams-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis into .gemini/skills/jams-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jams-data-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jams-data-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jams-data-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis .github/skills/jams-data-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "jams-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis into .github/skills/jams-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jams-data-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jams-data-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jams-data-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis .opencode/skills/jams-data-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "jams-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis into .opencode/skills/jams-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jams-data-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
jams-data-analysis- GitHub stars
- 1.2k
- Token cost
- ~1.9k tokens
- SKILL.md length
- 782 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when running and reporting the analysis for a Journal of the Academy of Marketing Science (JAMS) manuscript — selecting the estimator that matches the design (SEM/PLS, HLM…
- Regression/econometrics
- SKILL.md covers When to trigger, Choose the estimator that…, JAMS reporting conventions and Translate every result into a…, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Reporting effect sizes and uncertainty
What it does
Jams Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when running and reporting the analysis for a Journal of the Academy of Marketing Science (JAMS) manuscript — selecting the estimator that matches the design (SEM/PLS, HLM, regression/econometrics, experiments, meta-analysis), reporting effect sizes and uncertainty, and translating estimates into managerial magnitudes. Executes and reports; jams-methods designs the study and jams-contribution-framing states the payoff.
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Data & Analytics, covering Data analysis, Econometrics and empirical research and Translation. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- Regression/econometrics
- Reporting effect sizes and uncertainty
- Translating estimates into managerial magnitudes
Example prompts
- “/jams-data-analysis”
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Jams Data Analysis loads about 1.9k tokens when it runs. Until then it costs about 111 tokens; SKILL.md has 782 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 782 words, ~1,896 tokens.
Download SKILL.mdSave it as
.claude/skills/jams-data-analysis/SKILL.md (or your agent's skills folder).- name
- jams-data-analysis
- description
- Use when running and reporting the analysis for a Journal of the Academy of Marketing Science (JAMS) manuscript — selecting the estimator that matches the design (SEM/PLS, HLM, regression/econometrics, experiments, meta-analysis), reporting effect sizes and uncertainty, and translating estimates into managerial magnitudes. Executes and reports; jams-methods designs the study and jams-contribution-framing states the payoff.
Data Analysis & Reporting (jams-data-analysis)
When to trigger
- Data are collected and it is time to estimate and report
- You are unsure whether the estimator matches the design or the data structure
- A reviewer says "the analysis does not support the inference" or "report effect sizes"
- Significance is reported but the managerial magnitude is missing
Choose the estimator that matches the design
| Design / claim | Estimator |
|---|---|
| Latent constructs + structural paths (survey) | Covariance-based SEM (Mplus / lavaan / AMOS); PLS-SEM when prediction or formative constructs dominate |
| Nested data (consumers in stores, firms in industries) | HLM / multilevel models; random intercepts/slopes; report ICC |
| Mediation (process) | Bootstrapped indirect effects (PROCESS / lavaan), bias-corrected CIs; report the indirect effect, not just Baron–Kenny steps |
| Moderation / moderated mediation | Interaction term + simple slopes; conditional indirect effects (index of moderated mediation) |
| Experiment (factorial) | ANOVA / regression; estimated marginal means; planned contrasts; effect sizes per cell |
| Panel / observational causal | FE / DiD (modern staggered estimators); cluster-robust SE |
| Endogenous marketing regressor | IV/2SLS or Gaussian-copula control function; report first stage / instrument strength |
| Discrete choice / demand | Logit/probit; random-coefficient (mixed) logit |
| Meta-analysis | Random-effects effect-size synthesis; moderator meta-regression; publication-bias diagnostics |
Match SE clustering to the sampling/assignment structure (participant, store, market, firm).
JAMS reporting conventions
- APA results style. Report exact statistics (coefficients, SEs or t-values, CIs, exact p where shown). Avoid asterisk-only tables where the journal asks for precision; let the magnitude, not the star count, carry the result.
- Effect sizes and uncertainty, always. Standardized coefficients, R²/f², η²/Cohen's d, or odds ratios as the model requires — significance without magnitude is not a JAMS result.
- SEM reporting: measurement model first (loadings, AVE, CR, discriminant validity), then the structural model (standardized paths, R² for endogenous constructs, overall fit: CFI, TLI, RMSEA, SRMR).
- PLS reporting: loadings/weights, CR, AVE, HTMT, R², Q² (predictive relevance), and f²; bootstrap the path significances.
Translate every result into a managerial magnitude
This is the JAMS-distinguishing step. For each headline result, write a ledger row before drafting the results paragraph:
| Result | Theory point it supports | Required statistic | Managerial magnitude |
|---|---|---|---|
| Main path / treatment effect | which hypothesis / mechanism is confirmed | std. coef. + CI / d | sales lift, share, CLV, margin, retention, brand-equity points |
| Mediation (process) | which mechanism carries the effect | indirect effect + bias-corrected CI | why the process matters for the decision |
| Moderation (contingency) | when the effect strengthens/reverses | interaction + simple slopes | the managerial guardrail / segmentation rule |
| Robustness / alternative model | which threat (CMV, endogeneity) is reduced | same discipline as the main result | whether the conclusion's direction/size holds |
If the managerial-magnitude column is empty, the result is not yet ready for a JAMS results section.
Show full SKILL.md (365 more words)Show less
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. JAMS is empirical marketing with much survey-based SEM; the chain below serves causal / quasi-experimental designs and many-outcome corrections.
- Many outcomes / specifications:
romano_wolf(step-down FWER) orbenjamini_hochberg— report the adjusted threshold. - OVB sensitivity:
oster_delta/sensemakr. - Inference:
wild_cluster_bootstrap(few clusters),twoway_cluster/conley; multilevel data → cluster at the right level. - Re-fit off one handle:
audit_result(result_id)lists the missing checks and the exactsuggest_functionfor each. - Exhibits:
etable/did_summary_to_latexfrom 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.
Checklist
- Estimator matches design and data structure; SE clustering correct
- SEM: measurement model reported before structural; full fit indices given
- PLS: HTMT, R², Q², f² reported; paths bootstrapped
- Mediation via bootstrapped indirect effects with bias-corrected CIs
- Moderation: simple slopes + index of moderated mediation where relevant
- Effect sizes and uncertainty reported throughout (APA style)
- Every headline result has a managerial-magnitude translation
- Robustness addresses the design's specific threat (CMV / endogeneity / pre-trends)
Robustness that targets the design's real threat
Generic robustness ("we also ran model B") rarely persuades JAMS reviewers; the robustness must answer the specific threat to the genre's inference:
- Survey/SEM: rule out CMV with a marker-variable / CFA-marker model and report whether paths survive; test an alternative measurement specification; show results hold on a holdout or second sample.
- Secondary data: placebo tests, alternative instruments, pre-trend/parallel-trends evidence, sensitivity to the identifying assumption, and alternative fixed-effect structures.
- Experiment: replication across stimuli/samples, a confound-ruling-out study, and a test of the alternative-mechanism account.
- Meta-analysis: sensitivity to coding decisions, trim-and-fill / PET-PEESE for publication bias, and influence diagnostics for outlier studies.
State, for each robustness check, which threat it neutralizes — a list of checks with no mapped threat reads as box-ticking.
Anti-patterns
- Baron–Kenny causal-steps mediation instead of bootstrapped indirect effects
- Reporting fit indices but no standardized paths or R²
- Significance with no effect size and no managerial magnitude
- Ignoring nesting (consumers within stores) and clustering
- A weak/untested instrument, or endogeneity waved away
- Asterisk tables that hide the size of the effect
- Robustness checks listed with no statement of which threat each addresses
Output format
【Design】survey-SEM / PLS / HLM / experiment / panel-causal / choice / meta
【Estimator】matches design? SE clustering: [...]
【Measurement (if SEM/PLS)】AVE/CR/discriminant + fit/HTMT: pass/fix
【Effect sizes + uncertainty】reported (APA)? pass/fix
【Mediation/moderation】bootstrapped indirect / simple slopes: done?
【Managerial-magnitude ledger】every headline result translated? yes/fix
【Robustness】design-specific threat addressed: [...]
【Next skill】jams-contribution-framing© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Jams Data Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Jams Data Analysis this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.9k | Automated safety check: Pass | MIT | |
| Statsbrycewang-stanford/Auto-Empirical-Research-Skills | 4.5k | — | ~2k | Automated safety check: Pass | Custom licence | |
| Analyzebrycewang-stanford/Auto-Empirical-Research-Skills | 4.5k | — | ~2.2k | Automated safety check: Notes | Custom licence | |
| Jape Data Analysisfranklee16/academic-research-skills | 223 | 1 repos | ~629 | Automated safety check: Pass | None | |
| Joe Data Analysisfranklee16/academic-research-skills | 223 | 1 repos | ~933 | Automated safety check: Pass | None | |
| Mksc Data Analysisfranklee16/academic-research-skills | 223 | 1 repos | ~1.1k | Automated safety check: Pass | None |
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Categories
Questions about Jams Data Analysis
What does Jams Data Analysis do?
A skill your agent uses when running and reporting the analysis for a Journal of the Academy of Marketing Science (JAMS) manuscript — selecting the estimator that matches the design (SEM/PLS, HLM…. Jams Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when running and reporting the analysis for a Journal of the Academy of Marketing Science (JAMS) manuscript — selecting the estimator that matches the design (SEM/PLS, HLM, regression/econometrics, experiments, meta-analysis), reporting effect sizes and uncertainty, and translating estimates into managerial magnitudes.
When should I use Jams Data Analysis?
Jams Data Analysis fits situations like: regression/econometrics; reporting effect sizes and uncertainty; translating estimates into managerial magnitudes.
How do I install Jams Data Analysis in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jams-data-analysis -a claude-code`. Or copy the skill folder (Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/jams-data-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Jams Data Analysis in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jams-data-analysis -a codex`. Or copy the skill folder (Journal-of-the-Academy-of-Marketing-Science-Skills/skills/jams-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/jams-data-analysis in your project. Codex loads it when a task matches its description.
Can I use Jams Data Analysis in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jams-data-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jams-data-analysis, .gemini/skills/jams-data-analysis, .github/skills/jams-data-analysis and .opencode/skills/jams-data-analysis in your project.
What does Jams Data Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Jams Data Analysis is instructions for the agent only.
Does Jams Data Analysis access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Jams Data Analysis safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Jams Data Analysis use?
Jams Data Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Jams Data Analysis use?
About 1.9k tokens (SKILL.md is roughly 7.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Jams Data Analysis?
Skills that share tags, products or a category with Jams Data Analysis: Stats (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars), Analyze (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars), Jape Data Analysis (franklee16/academic-research-skills, 223 stars) and Joe Data Analysis (franklee16/academic-research-skills, 223 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Jams Data Analysis?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,228 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.