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poq-survey-design-and-measurement

Use when defending the survey design and measurement of a Public Opinion Quarterly (POQ) manuscript through the Total Survey Error framework — cover…

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Survey Design & Measurement (poq-survey-design-and-measurement)

This is the POQ core. Reviewers are survey scientists who will probe every link in the **Total Survey

Error (TSE)** chain. The design must credibly connect the hypotheses (poq-theory-and-hypotheses) to

data that measure what you claim, and you must be able to **disclose every methodological element to

AAPOR standards**. Defend each error source against the strongest alternative.

When to trigger

  • Specifying the sampling frame, questionnaire, mode, or weighting scheme
  • A reviewer questioned coverage, nonresponse, question wording, mode, or representativeness
  • Building the Appendix A: Disclosure Elements (do this here, not at the end)
  • Designing a survey experiment (wording/order split-ballot, conjoint, list experiment)

Walk the Total Survey Error chain

  • Coverage. Frame vs. target population; who is missed (online/RDD/ABS undercoverage). State the

target population precisely.

  • Sampling. Probability vs. nonprobability; stratification, clustering, PSUs; selection

probabilities. Nonprobability/online panels need an explicit representativeness argument.

  • Nonresponse. Report unit and item nonresponse; the **response rate computed per AAPOR Standard

Definitions** (say RR1–RR6 and show the disposition-code calculation); assess nonresponse bias, not

just the rate.

  • Measurement. Question wording, order, response scales, reference periods, social desirability,

acquiescence. Validate constructs; pretest (cognitive interviews, behavior coding).

  • Mode. Single vs. mixed mode; quantify and adjust for mode effects; do not conflate a mode

artifact with a substantive change.

  • Adjustment / weighting. Design weights, nonresponse adjustment, calibration/raking,

post-stratification (incl. MRP). Report what the weights correct for and the resulting design effect.

AAPOR disclosure (build Appendix A now)

POQ requires you to disclose — for all data reported — or link to public documentation: funding;

exact question wording; population under study; sample design; **method and dates of

collection; response rate and how it was calculated (AAPOR definitions); sample sizes and

precision of findings; and any design effect due to clustering and weighting**. Assemble these in

"Appendix A: Disclosure Elements" as you design — see poq-transparency-and-data-policy.

Survey experiments

  • Split-ballot wording/order experiments: randomize, report the manipulation, isolate the measurement effect.
  • Conjoint / list experiments / vignettes: pre-specify estimands; address attention checks and attrition.
  • Preregister design and primary analyses; report power/MDE.

The artifact-vs-effect test (POQ-specific)

For the headline result, write one sentence: *"If this were a survey artifact (coverage / nonresponse

/ wording / order / mode / weighting) rather than a real opinion signal, the data would look like ___;

instead they look like ___."* If you cannot, the design does not yet isolate the contribution.

Design audit table

Build a one-page audit before submission:

| TSE component | Design choice | Residual risk | Evidence or disclosure |

| --- | --- | --- | --- |

| Coverage | Frame and eligibility rule | Who is systematically absent? | Benchmark comparison or limitation |

| Sampling | Selection probabilities / panel recruitment | Selection into the sample | Weighting, calibration, or sensitivity |

| Nonresponse | Contact protocol and disposition codes | Nonresponse bias | AAPOR RR calculation plus bias check |

| Measurement | Wording, order, scale, translation | Construct mismatch or satisficing | Pretest/cognitive evidence and exact wording |

| Mode | Web/phone/mail/mixed mode | Mode-specific response pattern | Mode controls, split test, or caveat |

| Weighting | Design, nonresponse, calibration weights | Inflated variance / model dependence | Design effect and weighted/unweighted comparison |

The final article should not merely say these issues were considered; it should point readers to the appendix row, table, or supplement where each was handled.

Execution bridge (StatsPAI / Stata MCP)

Estimate and audit the design, don't only describe it. Full map:

[execution-with-mcp](../../../shared-resources/empirical-methods/execution-with-mcp.md). Public Opinion Quarterly is survey methodology and public opinion; the chain serves causal/experimental claims, while survey-design and measurement contributions use their own standards (sampling, weighting, measurement error).

  • detect_designrecommend → fit with as_handle=trueaudit_result.
  • Observational causal claims: staggered DiD (callaway_santanna / sun_abraham +

bacon_decomposition + honest_did_from_result); IV (effective_f_test +

anderson_rubin_ci); RDD (rdrobust + mccrary_test).

  • Experiments: randomization-based inference, romano_wolf for many-outcome

family-wise control, and mediate for mediation (not naive controlling-away).

  • Sensitivity: oster_delta / sensemakr for observational claims.

Report the effect size in interpretable units; route the full battery to the

appendix/supplement. A run end-to-end (synthetic data, real returns) is in the

[JF execution walkthrough](../../../Journal-of-Finance-Skills/resources/worked-examples/02-execution-walkthrough.md).

Anti-patterns

  • Reporting a response rate with no AAPOR definition or calculation shown
  • Treating a nonprobability online sample as representative with no argument or benchmark
  • Ignoring mode effects in a mixed-mode design; conflating mode artifacts with opinion change
  • Weighting the point estimate but ignoring weights/clusters in the variance (see poq-data-analysis)
  • Leaving Appendix A disclosure until submission
  • Naming the target population broadly while the frame covers only reachable or panelized respondents

Output format

【Target population & frame】coverage gaps named
【Sample design】probability/nonprobability; strata/clusters/PSUs
【Nonresponse】RR definition + value + bias assessment
【Measurement】wording/order/scale + validation + pretest
【Mode】single/mixed; mode effect handled?
【Weighting】what it corrects + design effect
【Artifact ruled out】the artifact-vs-effect sentence
【Design audit】TSE table complete; residual risks disclosed
【Appendix A started?】[Y/N]
【Next】poq-data-analysis

Supplementary resources

  • [../../resources/external_tools.md](../../resources/external_tools.md) — complex-survey, weighting, measurement, and pretesting tools
  • [../../resources/official-source-map.md](../../resources/official-source-map.md) — AAPOR disclosure elements and Standard Definitions

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