Statistical tests for biosimilarity based on relative distance between follow-on biologics for ordinal endpoints

Yoo, Myung Soo; Kim, Donguk

doi:10.29220/csam.2020.27.1.001

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…Further diagnostic checks via hypothesis tests could tell if lack of fit does exist or not. For instance, the tests suggested in Fagerland and Hosmer (2016), see also Jeong and Lee (2009); Yoo and Kim (2020).…”

Section: Empirical Applicationmentioning

confidence: 99%

A modification of McFadden's R² for binary and ordinal response models

Ugba

Gertheiss

2023

Communications for Statistical Applications and Methods

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A lot of studies on the summary measures of predictive strength of categorical response models consider the likelihood ratio index (LRI), also known as the McFadden-R 2 , a better option than many other measures. We propose a simple modification of the LRI that adjusts for the effect of the number of response categories on the measure and that also rescales its values, mimicking an underlying latent measure. The modified measure is applicable to both binary and ordinal response models fitted by maximum likelihood. Results from simulation studies and a real data example on the olfactory perception of boar taint show that the proposed measure outperforms most of the widely used goodness-of-fit measures for binary and ordinal models. The proposed R 2 interestingly proves quite invariant to an increasing number of response categories of an ordinal model.

show abstract

Section: Empirical Applicationmentioning

confidence: 99%

A modification of McFadden's R² for binary and ordinal response models

Ugba

Gertheiss

2023

Communications for Statistical Applications and Methods

View full text Add to dashboard Cite

show abstract

Section: Empirical Applicationmentioning

confidence: 99%

A Modification of McFadden's $R^2$ for Binary and Ordinal Response Models

Ugba¹,

Gertheiss²

2022

Preprint

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A lot of studies on the summary measures of predictive strength of categorical response models consider the Likelihood Ratio Index (LRI), also known as the McFadden-R 2 , a better option than many other measures. We propose a simple modification of the LRI that adjusts for the effect of the number of response categories on the measure and that also rescales its values, mimicking an underlying latent measure. The modified measure is applicable to both binary and ordinal response models fitted by maximum likelihood. Results from simulation studies and a real data example on the olfactory perception of boar taint show that the proposed measure outperforms most of the widely used goodness-of-fit measures for binary and ordinal models. The proposed R 2 interestingly proves quite invariant to an increasing number of response categories of an ordinal model.

show abstract

Statistical tests for biosimilarity based on relative distance between follow-on biologics for ordinal endpoints

Cited by 2 publications

References 15 publications

A modification of McFadden's R² for binary and ordinal response models

A modification of McFadden's R² for binary and ordinal response models

A Modification of McFadden's $R^2$ for Binary and Ordinal Response Models

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Statistical tests for biosimilarity based on relative distance between follow-on biologics for ordinal endpoints

Cited by 2 publications

References 15 publications

A modification of McFadden's R2 for binary and ordinal response models

A modification of McFadden's R2 for binary and ordinal response models

A Modification of McFadden's $R^2$ for Binary and Ordinal Response Models

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Product

Resources

About

A modification of McFadden's R² for binary and ordinal response models

A modification of McFadden's R² for binary and ordinal response models