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Ciencias de la vida, físicas y sociales · Habilidades y competencias laborales · SOC 19-3032 · 115 skills

Contexto de la ocupación

Estas tareas de O*NET describen la ocupación y aportan contexto a la asignación SOC; no significan que cada Skill de la lista realice todas las tareas.

Provide advice on best practices and implementation for selection.
Develop and implement employee selection or placement programs.
Analyze data, using statistical methods and applications, to evaluate the outcomes and effectiveness of workplace programs.

Las tareas de O*NET se muestran en su idioma de origen (inglés). Los datos de tareas se han extraído de O*NET® 29.1 Database de USDOL/ETA y se utilizan bajo CC BY 4.0.

Fuentes representativas

Una muestra limitada de Skills populares asignadas a esta ocupación, con un máximo de una por repositorio de GitHub. A continuación aparece la lista completa.

psychometric-assessment

a5c-ai/babysitter

Develop, validate, and adapt measurement instruments including factor analysis, reliability testing, and cross-cultural validation

amj-data-analysis

brycewang-stanford/Awesome-Journal-Skills

Use when running and reporting the statistical analysis for an Academy of Management Journal (AMJ) manuscript — measurement validity, common-method bias, the right estimator (HLM, SEM, panel, experiments), endogeneity, and robustness. Executes and reports the analysis; it does not design the study (amj-methods) or frame the contribution (amj-contribution-framing).

Todas las Skills asignadas

Explora la asignación completa por popularidad del repositorio o actividad reciente de la fuente.

Los nombres y las descripciones conservan el idioma proporcionado por el repositorio de origen.

Ordenar por

psychometric-assessment

a5c-ai/babysitter

Develop, validate, and adapt measurement instruments including factor analysis, reliability testing, and cross-cultural validation

amj-data-analysis

brycewang-stanford/Awesome-Journal-Skills

Use when running and reporting the statistical analysis for an Academy of Management Journal (AMJ) manuscript — measurement validity, common-method bias, the right estimator (HLM, SEM, panel, experiments), endogeneity, and robustness. Executes and reports the analysis; it does not design the study (amj-methods) or frame the contribution (amj-contribution-framing).

brycewang-stanford/Awesome-Journal-Skills

Use when the research design and method are the bottleneck for an Academy of Management Journal (AMJ) manuscript — matching design (archival, survey, experiment, multi-method, field) and level of analysis to the theoretical question. Designs the study; it does not run the estimation or validity checks (amj-data-analysis).

joap-data-analysis

brycewang-stanford/Awesome-Journal-Skills

Use when analyzing and reporting results for a Journal of Applied Psychology (JAP) manuscript using SEM, multilevel (HLM) models, mediation/moderation, or meta-analysis. JAP requires effect sizes with confidence intervals, model-based indirect effects with bootstrap CIs, fit indices, full disclosure, and a clean confirmatory/exploratory split. Guides analysis norms; it does not fabricate results.

joap-study-design

brycewang-stanford/Awesome-Journal-Skills

Use when designing studies and measurement for a Journal of Applied Psychology (JAP) manuscript so they meet the journal's high bar on construct validity, causal inference, common-method variance, nested/multilevel data, and sample-size justification. Strengthens the design and measurement plan; it does not write code.

joap-tables-figures

brycewang-stanford/Awesome-Journal-Skills

Use when building tables and figures for a Journal of Applied Psychology (JAP) manuscript in APA 7th-edition style — correlation/descriptives tables, CFA/SEM path diagrams, multilevel (HLM) result tables, and meta-analytic forest/funnel plots. Exhibits must carry effect sizes, CIs, and reliabilities and be self-contained. Designs exhibits; it does not run the analysis.

jcp-data-analysis

brycewang-stanford/Awesome-Journal-Skills

Use when analyzing experimental data for a Journal of Consumer Psychology (JCP) manuscript — ANOVA/regression on the effect, measured and experimental mediation, moderation and moderated mediation, measurement of the process, and the rigor-era reporting standards. Analyzes the studies; it does not design them (jcp-methods).

brycewang-stanford/Awesome-Journal-Skills

Use when designing or stress-testing the experiments for a Journal of Consumer Psychology (JCP) manuscript — manipulations, controls and confounds, manipulation checks, power, the multi-study chain, and pre-registration. Designs the studies that test the process; it does not analyze them (jcp-data-analysis).

jcp-tables-figures

brycewang-stanford/Awesome-Journal-Skills

Use when building the exhibits for a Journal of Consumer Psychology (JCP) manuscript — condition-means tables, mediation/moderation path figures, interaction plots, and APA-formatted statistical reporting that makes the process visible. Builds the exhibits; it does not run the analysis (jcp-data-analysis).

jcr-data-analysis

brycewang-stanford/Awesome-Journal-Skills

Use when running and reporting the evidence for a Journal of Consumer Research (JCR) manuscript — process evidence (mediation/moderation) for behavioral experiments, or trustworthy interpretation for Consumer Culture Theory (CCT) work — plus robustness and the transparency reporting JCR requires. Executes and reports; it does not design the studies (jcr-methods).

brycewang-stanford/Awesome-Journal-Skills

Use when choosing or stress-testing the research design for a Journal of Consumer Research (JCR) manuscript — multi-study behavioral experiments, interpretive Consumer Culture Theory (CCT) fieldwork, mixed designs, or a Registered Report — so the evidence matches the conceptual claim. Designs the studies; it does not analyze them (jcr-data-analysis).

jcr-tables-figures

brycewang-stanford/Awesome-Journal-Skills

Use when building the exhibits for a Journal of Consumer Research (JCR) manuscript — study-summary tables, mediation/moderation results, interaction and spotlight plots, conceptual/process figures, and CCT data displays — in Chicago house style, mindful of the 60-page embedding rule and the web appendix. Late-stage polish; settle the contribution first (jcr-contribution-framing).