An Improved Satterthwaite (1941, 1946) Effective <i>df</i> Approximation

This study introduces a correction to the approximation of effective df as proposed by Satterthwaite, specifically addressing scenarios where component df are small. The correction is grounded in analytical results concerning the moments of standard normal random variables. This modification is applicable to complex variance estimates that involve both small and large df , offering an enhanced approximation of the higher moments required by Satterthwaite’s framework. Additionally, this correction extends and partially validates the empirically derived adjustment by Johnson and Rust, as it is based on theoretical foundations rather than simulations used to derive empirical transformation constants. Finally, the proposed adjustment also provides a correction to the estimate of the total variance in cases missing data have been replaced by multiple imputations such as in the case of plausible values in national and international large scale assessments.

Authors

Institutions

Publication Details

Journal
Journal of Educational and Behavioral Statistics
Published
2025-01-27
DOI
https://doi.org/10.3102/10769986241309329
Citations
1
Primary Topic
Statistical Methods and Bayesian Inference
Type
article
Field-Weighted Citation Impact
2.63
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Improved Satterthwaite (1941, 1946) Effective df Approximation

Matthias von Davier
1 citations
Journal of Educational and Behavioral Statistics
Statistical Methods and Bayesian Inference
2.63
article

An Improved Satterthwaite (1941, 1946) Effective df Approximation

Matthias von Davier
article en
1 citations

Abstract

This study introduces a correction to the approximation of effective df as proposed by Satterthwaite, specifically addressing scenarios where component df are small. The correction is grounded in analytical results concerning the moments of standard normal random variables. This modification is applicable to complex variance estimates that involve both small and large df , offering an enhanced approximation of the higher moments required by Satterthwaite’s framework. Additionally, this correction extends and partially validates the empirically derived adjustment by Johnson and Rust, as it is based on theoretical foundations rather than simulations used to derive empirical transformation constants. Finally, the proposed adjustment also provides a correction to the estimate of the total variance in cases missing data have been replaced by multiple imputations such as in the case of plausible values in national and international large scale assessments.

Journal of Educational and Behavioral StatisticsVol. 51(1)
Boston College (US)
Openalex Percentile: Top 15%
Statistical Methods and Bayesian Inference
2.63
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.