A unified framework for significance testing in fractional factorials.

DOI10.1016/S0167-9473(98)90151-7zbMath1042.62591OpenAlexW4229941608MaRDI QIDQ1274835

Tormod Næs, Øyvind Langsrud

Publication date: 12 January 1999

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-9473(98)90151-7

zbMATH Keywords

Subset selectionExperimental designMonte Carlo testingChain-poolingProbability plottingRealistic model strategy

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Factorial statistical designs (62K15)

Related Items (8)

A powerful test method for analyzing unreplicated factorials ⋮ An analysis of three-level orthogonal saturated designs ⋮ A note on step-up test in orthogonal saturated designs ⋮ Step-up test with a single cutoff for unreplicated orthogonal designs ⋮ Step-up simultaneous tests for identifying active effects in orthogonal saturated designs ⋮ Analyzing Designed Experiments with Multiple Responses ⋮ The analysis of unreplicated factorial experiments from a geometric perspective ⋮ Control of error rates in adaptive analysis of orthogonal saturated designs.

Cites Work

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• A Hypothesis-Testing Approach toward Identifying Active Contrasts
• Generalized modulus-ratio tests for analysis of factorial designs with zero degrees of freedom for error
• An Analysis for Unreplicated Fractional Factorials
• "Chain pooling" model selection for two-level fixed effects factorial experiments
• Inference for Effect-Saturated Fractional Factorials

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