alterlab-ssci-sampling-gate
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Gates who is sampled, how, and how many before data collection — checks that the sampling FRAME matches the target population (coverage error), that the METHOD is named (probability vs non-probability: simple random, stratified, cluster, systematic, quota, convenience, snowball), that sample SIZE follows the inference paradigm (an a-priori power analysis for hypothesis tests, a precision/margin-of-error target for estimation, or saturation/information power for qualitative studies — never a rule of thumb or collect-until-significant), and that the generalization claim matches the sample (statistical generalization only from probability samples). Use when asking how many participants are needed, planning recruitment, running or checking a power analysis, or judging whether a sample supports a population claim. For questionnaire items prefer alterlab-survey-design; for choosing the statistical test prefer alterlab-test-selection-guard. Part of the AlterLab Academic Skills suite.
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npx skills add AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-ssci-sampling-gate -a claude-code
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Similar skills
Closest to this one by what they do and when they are used.
- alterlab-ssci-inference-gateAlterLab-IEU/AlterLab-Academic-SkillsAudits final inferential claims against the design, sample, and uncertainty before they are written or published — refuses causal language unless the design's identifying assumption is defended (else downgrades to associational), corrects p-value and confidence-interval misreadings (a p-value is not the probability the null is true, non-significance is not proof of no effect, a 95% CI is not a 95% probability the parameter is inside it), demands effect sizes with intervals rather than significance stars, flags uncorrected multiple comparisons and optional stopping / HARKing, and scopes generalization to the sampling frame. Use when writing or checking a results or discussion section, interpreting a p-value or confidence interval, or deciding whether a finding supports a causal or population claim. For choosing the statistical test prefer alterlab-test-selection-guard; to execute the analysis prefer alterlab-statistical-analysis. Part of the AlterLab Academic Skills suite.Testing★ 78
- alterlab-ssci-measurement-gateAlterLab-IEU/AlterLab-Academic-SkillsGates measurement quality before a scale or instrument is trusted — checks that each construct is defined and operationalized, that reliability is evidenced with McDonald omega (not Cronbach alpha alone, which assumes tau-equivalence and is only a lower bound), that reliability is not confused with validity (content, criterion, convergent/discriminant construct validity), and that measurement invariance is tested before comparing groups. Use when asking whether a scale or survey instrument is valid, reporting a Cronbach alpha, building or adopting a multi-item measure, or comparing a latent construct across groups. For designing the questionnaire items prefer alterlab-survey-design; for running the confirmatory factor analysis prefer alterlab-sem-psychometrics; to execute basic statistics prefer alterlab-statistical-analysis. Part of the AlterLab Academic Skills suite.Design★ 78
- alterlab-ssci-design-gateAlterLab-IEU/AlterLab-Academic-SkillsRoutes a social-science study to its research design — true experiment, quasi-experiment (difference-in-differences, instrumental variables, regression discontinuity, interrupted time series, fixed effects), observational/correlational, qualitative, or mixed — by walking the random-selection and random-assignment decisions, then PINS the identifying assumption the causal claim will rest on (parallel trends, exclusion restriction, continuity at the cutoff, selection-on-observables, or qualitative saturation logic) before any analysis begins. Use when choosing a study design, asking what design to use, framing a causal question from observational data, or deciding experiment vs quasi-experiment vs observational. For executing the analysis prefer alterlab-statistical-analysis; for qualitative design depth prefer alterlab-qualitative-methods; for choosing the statistical test downstream prefer alterlab-test-selection-guard. Part of the AlterLab Academic Skills suite.Design★ 78
- alterlab-ssci-reflexivity-gateAlterLab-IEU/AlterLab-Academic-SkillsGates trustworthiness before qualitative or interpretivist claims are written — the qualitative analog of the measurement gate. Checks that researcher positionality and role are stated, that the four Lincoln & Guba trustworthiness criteria are addressed (credibility via triangulation / member-checking / prolonged engagement, transferability via thick description, dependability via an audit trail, confirmability via reflexive bracketing), and that reflexivity is evidenced rather than asserted. Fail-closed: interpretivist generalizing or causal language is refused without the corresponding warrant. Use when a study is qualitative / ethnographic / interpretivist, when reviewing trustworthiness or reflexivity, or before writing up thematic or grounded-theory findings. For quantitative measurement validity prefer alterlab-ssci-measurement-gate; for running the coding prefer alterlab-qualitative-analysis; for the final claim audit prefer alterlab-ssci-inference-gate. Part of the AlterLab Academic Skills suite.Writing★ 78
- alterlab-test-selection-guardAlterLab-IEU/AlterLab-Academic-SkillsEnforces statistical-test selection as a discipline, holding the Iron Law NO TEST CHOSEN AFTER SEEING THE P-VALUE: routes the choice through a fixed decision tree (outcome type -> groups -> paired? -> normality) terminating in named tests (t-test, Mann-Whitney U, ANOVA, Kruskal-Wallis, Wilcoxon, Friedman, chi-square, Pearson/Spearman, regression), gates interpretation behind a mandatory Shapiro-Wilk/Levene/linearity assumption check, blocks test-shopping with an Excuse-vs-Reality table and Red-Flags-STOP list, and applies a 3+-tests escalation gate forcing Bonferroni/FDR correction or an exploratory label. Use when choosing or switching a statistical test, asking which test to run, dropping a test after a non-significant result, or running many tests hunting for significance. For executing the chosen test prefer alterlab-statistical-analysis or alterlab-statsmodels; for the broader frozen-plan discipline see alterlab-preregistration-discipline. Part of the AlterLab Academic Skills suite.Testing★ 78
- alterlab-ssci-orchestratorAlterLab-IEU/AlterLab-Academic-SkillsCoordinates a social-science study through the stage-gated methods pipeline — question then design-gate then measurement-gate then sampling-gate then the right analysis module then inference-gate then reporting — holding a single YAML Design Passport that each gate reads and appends, and enforcing gate order with PASS / WARN / BLOCK semantics (design-gate and inference-gate are fail-closed). It is thin: it routes and holds the artifact, it does not run analysis itself. Use when a researcher describes a whole social-science study end to end, asks to run the methods pipeline or a full methodology review, or wants the design-to-inference workflow coordinated rather than a single step. For a single stage trigger that gate directly (alterlab-ssci-design-gate, -measurement-gate, -sampling-gate, -inference-gate); for multi-agent execution mechanics see alterlab-workflow-orchestration. Part of the AlterLab Academic Skills suite.Design★ 78
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