joc-research-design

Research Design (joc-research-design)

JoC accepts many methodologies but is demanding about each. The design must credibly connect the

argument (joc-theory-building) to evidence. This skill is mode-aware: pick the section that matches

your work and defend it against the strongest alternative explanation.

When to trigger

• Specifying an experiment, survey, content-analysis protocol, computational pipeline, or fieldwork plan
• A reviewer questioned causal claims, sampling, coding reliability, validity, or a confound
• Preparing a preregistration / pre-analysis plan (note it in the cover letter)
• Justifying why your design adjudicates the rival account from joc-literature-positioning

Experiments (lab / online / survey / field)

• Preregister the design and primary analyses; report a-priori power / MDE; pre-specify subgroups.
• Treatment realism and ecological validity; manipulation and attention checks; attrition.
• Stimuli sampling: treat messages as a sample, not a fixture (consider stimulus-as-random-factor).
• Ethics/IRB and informed consent; debrief where deception is used.

Surveys / panels

• Sampling frame, mode, and generalization claims; weighting where appropriate.
• Validated multi-item measures; report reliability; guard against common-method variance.
• For cross-sectional mediation, be explicit about causal limits; prefer panel/experimental designs for process claims.

Content analysis

• A documented codebook; trained coders; report intercoder reliability (Krippendorff's alpha or

equivalent) on an adequate subsample, and the unit of analysis.

• Sampling of texts justified (timeframe, sources); construct validity of categories.

Computational / text-as-data

• Validate automated measures against human-coded gold-standard samples; report agreement.
• Document model/version, hyperparameters, seeds; report stability; do not treat outputs as ground truth.
• Address platform/ToS and ethics for collected data.

Qualitative / critical

• Justify case/site/text selection by design logic, not convenience; say what it is a case of.
• Trustworthiness: reflexivity, audit trail, transparent coding; state what evidence would complicate the reading.

The adjudication test (JoC-specific)

For the single strongest rival explanation, write one sentence: *"If the rival were true rather

than my argument, the data would look like ___; instead they look like ___."* If you cannot, the

design does not yet identify the contribution.

Reviewer-pushback patterns and the JoC-specific fix

JoC referees at the ICA flagship rarely reject on a single statistic; they reject when the design

cannot bear the theoretical weight the paper puts on it. The recurring objections and their

venue-specific repairs:

| Reviewer objection | Why it lands at JoC | Design-stage fix |

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

| "Single-message confound" | one stimulus cannot separate the message feature from the specific text | sample multiple messages per condition; treat message as a random factor; report a stimulus-sampling check |

| "Measurement validity of message features" | a hand-coded or model-coded "frame" may not be the construct claimed | pre-validate the feature against human gold-standard coding; report construct validity, not just reliability |

| "Effect without mechanism" | a main effect alone does not advance communication theory | design the mediator/moderator measurement in before collection; pre-specify the indirect-effect test |

| "Exposure is assumed, not measured" | self-reported "saw the news" is a weak proxy | build a behavioral or attention-anchored exposure measure |

| "Cross-sectional process claim" | mediation on one wave cannot license a causal story | move the mediator to an experiment or panel, or hedge the claim |

Worked micro-example: framing survey-experiment design (illustrative)

A planned study claims that gain- vs. loss-framed vaccine messages change intention via

perceived risk. A JoC-defensible design: 2 (frame) × 3 (message exemplars per frame) factorial

so the frame effect is estimated across six distinct texts, not one — defeating the single-message

confound. Target N ≈ 900 (illustrative; size to the registered MDE), preregister the mediation

path frame → perceived risk → intention with bootstrap CIs, and add an attention check plus a

behavioral exposure proxy. The adjudication sentence writes itself: if the rival "any health message

moves intention" were true, the gain/loss contrast would be null while overall intention rose;

instead the contrast is non-null and runs through perceived risk — advancing framing theory rather

than re-documenting a persuasion effect.

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). Journal of Communication spans experiments, surveys, and content analysis; randomization inference for experiments, DiD/IV for observational media-effects claims.

• detect_design → recommend → fit with as_handle=true → audit_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

• Causal language on a cross-sectional survey that only supports association
• Content analysis with no reported intercoder reliability or an unstated unit of analysis
• Automated text measures used without human validation
• Convenience case/stimulus selection dressed up as theory-driven
• A single-message stimulus carrying a claim about a message feature
• A design that cannot distinguish your argument from the leading alternative

Output format

【Mode】experiment / survey / content-analysis / computational / qualitative
【Estimand or claim】what is being identified/shown
【Key assumption(s)】and how each is defended (incl. reliability/validity)
【Rival ruled out】the adjudication sentence
【Robustness/sensitivity】planned checks
【Next】joc-data-analysis

Supplementary resources

• [../../resources/external_tools.md](../../resources/external_tools.md) — design, reliability, and text-as-data packages (R/SPSS/Mplus/Python) and CAQDAS for qualitative work
• [../../resources/official-source-map.md](../../resources/official-source-map.md) — preregistration and Open Science Badge notes