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WFC - Workflow-Oriented Survey Weight Calibration

Provides a disciplined precheck, execution, and diagnostics workflow for survey weighting and raking. Weight construction requires design-only data, a verified external target, outcome-blind planning, and human approval before weight locking, with bilingual reports for decision and statistical audiences. Converts calibrated and replicate weights into standard survey designs, provides optional broom-style result projections, and records serializable production pipeline provenance. Supports fixed, predeclared soft calibration tolerances and categorical entropy balancing from verified margins, plus panel attrition weighting, high-influence unit diagnostics, Fay's balanced repeated replication, and opt-in parallel execution for long runs. Calibration methods follow Deville and Saerndal (1992) <doi:10.1080/01621459.1992.10475217>, and entropy balancing follows Hainmueller (2012) <doi:10.1093/pan/mpr025>.

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5.18 score 3 scripts 320 downloads

DCC - Data Cleaning Center for Survey and Assessment Data

Rule-driven, auditable cleaning of survey and assessment response data, implementing the WeianData Detect-Execute-Report workflow. Provides a multi-format, multi-encoding input layer (CSV, 'Excel', 'SPSS', 'Stata', 'SAS', Parquet, JSON), the dcc_data container with a provenance chain, level-0 structural diagnostics, five built-in response-quality detectors (missing items, straight-lining, response time, trap items, score anomalies), a declarative YAML rule engine, an execution engine with a cell-level audit log, answer-key scoring, multi-form to master item bank mapping, a normalized report model rendered as bilingual staff workbooks and HTML, complete statistical bundles, and versioned machine JSON/JSONL with findings-to-changes reconciliation, cell-level lineage tracing, and manifest-based one-command reproduction. Includes a protected bilingual strict project workbook and matching JSON contract with cell-addressed validation, non-mutating preflight, preview-first execution, and localized staff guidance. All formally supported input backends install with the package; PDF is optional rather than a fixed report output.

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4.70 score

LISTC - Pivot-Style Statistical Tables for Large-Scale Assessment Data

Turns assessment and survey sample data (demographics, scores, sampling weights, ability estimates with individual item response theory standard errors, replicate weights and plausible values) into fully customizable pivot-style statistical tables in which every cell carries a design-appropriate standard error. Provides weighted means, proportions above cut scores, proficiency-level percentages and quantiles; sampling variance via linearization, Woodruff (1952) <doi:10.1080/01621459.1952.10483443> intervals for quantiles, or balanced repeated replication and jackknife replicate weights including Fay's method; measurement variance via delta-method propagation of individual standard errors or Rubin (1987) <doi:10.1002/9780470316696> combination across plausible values. Imports data from 'CSV', 'Excel', 'SPSS', 'SAS', 'Stata' and item response theory software person files ('Winsteps', 'ConQuest'); a configuration-file interface serves non-programmers and automation; results export to formatted 'Excel', 'JSON' and standalone 'HTML' reports with rule-based plain-language interpretation.

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4.00 score 300 downloads

IRTC - Marginal Maximum Likelihood Estimation for Item Response Models

Self-contained marginal maximum likelihood (MML) estimation for unidimensional and multidimensional item response models, including the Rasch / one-parameter logistic, partial credit, rating scale, two-parameter logistic and generalised partial credit models, with latent regression, multiple groups and case weights. A parallelised, dimension-factorised streaming estimation engine supports large between-item (simple-structure) multidimensional models with bounded memory and an opt-in controlled-accuracy quadrature mode that reports a measured approximation error. A usability layer serves non-specialists and automated pipelines: one-stop estimation from common file formats ('Excel', delimited text, 'SPSS', 'Stata', 'SAS') with automatic cleaning and answer-key scoring, pre-estimation data checks, classical item statistics and item fit, plain-language quality ratings, bilingual (English/Chinese) output, spreadsheet exports for item banking and cross-year linking, audience-specific 'Word'/'HTML' reports, and machine-readable results with structured error conditions. Methods follow Adams, Wilson and Wang (1997) <doi:10.1177/0146621697211001>.

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cpp

3.30 score 319 downloads