The authors develop npd residuals for categorical data via jittering, show through simulations that they detect structural and parameter misspecifications, compare performance to chi-square tests, and demonstrate utility on a real toenail infection dataset.
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npde methods extend to joint longitudinal-TTE models via censored data imputation and a combined test that maintains ~5% type I error while detecting misspecifications in prostate cancer simulations.
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Development and performance of npd for the evaluation of models with ordinal data
The authors develop npd residuals for categorical data via jittering, show through simulations that they detect structural and parameter misspecifications, compare performance to chi-square tests, and demonstrate utility on a real toenail infection dataset.
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Evaluation of the npde performance for the evaluation of joint model with longitudinal and TTE data: an application in metastatic hormono-resistant prostate cancer
npde methods extend to joint longitudinal-TTE models via censored data imputation and a combined test that maintains ~5% type I error while detecting misspecifications in prostate cancer simulations.