pisa-international

What problem does it solve?

This Skill helps you analyze PISA/TIMSS international large-scale assessment data correctly, including plausible-value aggregation and replicate-weight (BRR) uncertainty.

Core Features & Use Cases

• Plausible-values correct country estimates: Computes country-level mean performance by combining all 10 plausible values using Rubin’s rules.
• Fay BRR variance estimation: Estimates sampling variance using 80 BRR replicate weights with the correct Fay coefficient (k=0.5).
• SES gradients and cross-national comparisons: Fits ESCS (SES) gradient regressions and supports valid cross-country figures with uncertainty.

Use Case: You want to compare math performance across multiple countries while reporting confidence intervals that reflect both sampling variability and imputation variability from plausible values.

Quick Start

Use this Skill to compute PISA math country means with BRR-based standard errors from a PISA 2022 student dataset containing PV1MATH–PV10MATH and W_FSTR1–W_FSTR80.