| name | etp-data-analysis |
| description | Use when executing or defending the analysis for an Entrepreneurship Theory and Practice (ETP) manuscript — estimation, event-history, SEM, endogeneity, and qualitative coding rigor, with the new-venture inference problems front of mind. |
Data Analysis (etp-data-analysis)
When to trigger
- The estimator is chosen but endogeneity, selection, or survivorship is not yet addressed in the numbers
- You used TWFE/OLS on staggered or time-varying venture data without checking for bias
- A time-to-event outcome (founding, exit, failure, IPO) is modeled with a linear regression
- A reviewer asks for robustness, an alternative specification, or an IV/control-function
- Qualitative coding needs an analysis plan a methods reviewer will accept
The ETP analysis bar
ETP wants analysis that the theory can stand on and that survives the new-venture inference traps.
Because the journal is method-plural, "analysis" differs by branch — but every branch must (a) match the estimator to the outcome and the entrepreneurial data structure, (b) confront endogeneity/selection head-on, and (c) report uncertainty honestly.
ETP house style follows APA: report effect sizes and confidence intervals, not a forest of significance asterisks standing in for substance.
Branch paths
Quantitative — outcome-appropriate estimation
- Time-to-event (founding, exit, failure, IPO): use survival / event-history (Cox, discrete-time hazard, competing risks).
Modeling "did it exit (0/1)" with OLS throws away timing and censoring information.
- Counts / rare events (patents, hires, funding rounds): negative binomial / zero-inflated where overdispersion or excess zeros bite, not OLS.
- Bounded / proportion outcomes (survival rate, equity share): fractional/beta models, not naive linear.
- Panel with staggered timing (policy/financing shocks across cohorts): beyond TWFE — Callaway–Sant'Anna, Sun–Abraham — with a clean event-study and pre-trend evidence.
Endogeneity and selection (the ETP reflex)
- Selection into founding / survival: Heckman / control-function when the sample conditions on success; report the exclusion restriction's logic.
- IV: strong first stage; with weak instruments use weak-IV-robust inference; defend exclusion in institutions and theory, not just statistically.
- Reverse causality (does growth cause financing or vice versa): lagged designs, shocks, or dynamic panel (system-GMM) with instrument-count discipline.
SEM / measurement models
- Report CFA fit (CFI, RMSEA, SRMR), composite reliability, AVE, and discriminant validity (HTMT) for entrepreneurial constructs; test common-method bias when self-report dominates (marker variable, not just Harman's single factor).
Qualitative analysis
- A transparent coding scheme, the Gioia data structure as an exhibit, inter-coder agreement where appropriate, and traceability from quotation → code → theoretical dimension.
The output is a process model, not a code count.
Make the magnitude mean something for practice
ETP's dual mandate reaches the results: translate coefficients into the venture-relevant scale (a hazard ratio as "ventures with X fail 30% faster," a marginal effect as "one more co-founder shifts funding probability by Y points").
A practitioner implication needs a magnitude, not a p-value.
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. ETP is entrepreneurship, where selection and survival bias are pervasive — foreground identification and selection corrections.
- Many outcomes / specifications:
romano_wolf (step-down FWER) or
benjamini_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
exact suggest_function for each.
- Exhibits:
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.
Checklist
Anti-patterns
- Linear regression on a time-to-event outcome (ignores censoring and timing)
- Selection/survivorship acknowledged in prose but absent from the model
- Asterisk theater — significance stars substituting for effect sizes and CIs
- Naive TWFE on staggered venture/policy data with no heterogeneity-bias check
- Harman's single factor offered as if it settled common-method bias
- Code counts presented as if they were a process theory
Worked vignette (illustrative)
A team wants to test whether accelerator participation raises venture survival, using cohorts admitted across several years and a binary "survived to year 3" outcome.
The first draft runs OLS on the 0/1 outcome with year and region controls.
Three ETP-specific upgrades: (1) the outcome is fundamentally time-to-event — recast as a discrete-time hazard or Cox model with competing risks (acquired vs. shut down vs. still operating), recovering the timing and censoring OLS discards; (2) accelerators select promising ventures, so survival differences may be selection, not treatment — exploit a plausibly exogenous admission threshold (a scoring cutoff supports a regression-discontinuity or fuzzy-RD design) rather than controls alone; (3) because cohorts enter in staggered years and the program changed over time, a naive two-way fixed-effects "treatment" coefficient can be biased — use a modern staggered-DID estimator with a pre-trend check.
Finally, report the hazard ratio with a CI and translate it: "admitted ventures fail roughly 25% slower over three years," a magnitude an accelerator director can act on.
Output format
【Journal】Entrepreneurship Theory and Practice
【Branch】quantitative / SEM / qualitative
【Outcome→estimator】outcome type + matched model
【Selection/survivorship】how addressed in the numbers
【Endogeneity】IV / control-function / lagged / dynamic panel + exclusion logic
【Inference】effect sizes + CIs (APA); CMB if self-report
【Magnitude for practice】coefficient translated to venture scale
【Next skill】etp-contribution-framing
