Spq Data Analysis

---
name: spq-data-analysis
description: Use when executing and reporting the analysis for a Social Psychology Quarterly (SPQ) manuscript so it survives expert, masked review — honest uncertainty, robustness, sound measurement, and reporting appropriate to experiments, surveys/secondary data, or interpretive analysis in sociological social psychology. Guides analysis norms; it does not fabricate results.
---

# Data Analysis (spq-data-analysis)

SPQ reviewers are sophisticated about both social-psychological measurement and the methods of each
tradition. Analyze and report so an expert can trust the result and see the **structure–individual link**
in the numbers (or the interpretation). This skill covers execution and reporting norms; design decisions
live in `spq-research-design`.

## When to trigger

- Running main and supporting analyses; building the results section
- A reviewer asked for robustness, heterogeneity, alternative measures, or model checks
- Reconciling preregistered (where used) vs. exploratory analyses
- Reporting measurement quality for latent social-psychological constructs

## Analysis norms SPQ expects

1. **Report uncertainty honestly.** Confidence/credible intervals, not just stars; the **magnitude** and
   substantive meaning of the estimate, in the metric of the construct, not just significance.
2. **Measurement quality up front.** For identity salience, mastery, sentiment, status, etc.: report
   reliability (alpha/omega), and where relevant CFA/SEM fit; show the result is not a scaling artifact.
3. **Robustness that probes, not decorates.** Alternative measures, samples, model specifications, or
   estimators that could *break* the result — and say what you learn.
4. **Right inference for the design.** Survey weights/clustering for complex samples; multilevel models
   for individuals nested in groups/contexts; randomization-appropriate inference for experiments;
   multiple-comparison adjustment when testing many implications.
5. **Heterogeneity with discipline.** Pre-specify subgroups where possible; don't mine for a significant
   interaction and theorize it post hoc.
6. **Mediation/mechanism with care.** If you claim the social-psychological mechanism mediates, test it
   properly (modern mediation/sensitivity), and acknowledge the assumptions.

## Interpretive / qualitative specifics
- Make the analytic procedure transparent: coding scheme, how themes/categories were derived, negative cases.
- Show how the evidence (interaction excerpts, fieldnotes, accounts) supports the claim; quote enough to let the reader judge.

## Reproducibility while you work (good practice, not a gate)
- A **master script** that regenerates every table and figure from the (raw or constructed) data.
- **Set and report seeds** for any stochastic step (bootstrap, simulation, multiple imputation).
- Pin software/package versions (`renv.lock`, `requirements.txt`, recorded installs).
- Keep table/figure numbers matched to outputs. SPQ **encourages** sharing materials but does not require
  it (see `spq-data-and-transparency`) — still analyze reproducibly for your own sake and the reviewers'.

## Anti-patterns

- Stars-only tables with no effect sizes or intervals
- Reporting an effect on a construct whose reliability/validity is never shown
- "Robustness" that only reruns near-identical specs to manufacture stability
- p-hacking / fishing for a significant interaction; HARKing exploratory results into hypotheses
- Ignoring clustering/weighting in complex-survey or nested-group data
- Quoting one vivid excerpt as if it established a pattern (interpretive work)

## Output format

```
【Main estimate / claim】magnitude + interval (or analytic claim) + substantive meaning
【Measurement】reliability/validity of key constructs reported? [Y/N]
【Inference correct for design?】weighting/clustering/multilevel/randomization [note]
【Robustness】specs that could break it → what held
【Heterogeneity】pre-specified? adjusted?
【Reproducible】master script + seeds + pinned versions? [Y/N]
【Next】spq-tables-figures
```

## Supplementary resources

- [`../../resources/external_tools.md`](../../resources/external_tools.md) — estimation, measurement (SEM/reliability), and CAQDAS packages
- [`../../resources/official-source-map.md`](../../resources/official-source-map.md) — data-and-materials policy (encouraged, not required)