Mathematics
8 years ago

Biased hypothesis sum of squares distorts linear model testing accuracy.

Communication in Statistics- Theory and Methods
Distribution of the biased hypothesis sum of squares in linear models with missing observations
Anant M. Kshirsagar, Sheela S. Deo

Paper Summary

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The article explores how linear models with missing data can lead to biased results when testing hypotheses about parameters. By deriving the distribution of these biased results, the researchers found that using them can affect the accuracy of Type I and Type II errors in statistical analysis.