Nonparametric Survival Analysis: Cox-Mantel tests and Permutation tests

Permutation tests for nonparametric detection

In this paper, the authors provide a methodology to design nonparametric permutation tests and, in particular, nonparametric rank tests for applications in detection. In the first part of the paper, the authors develop the optimization theory of both permutation and rank tests in the Neyman-Pearson sense; in the second part of the paper, they carry out a comparative performance analysis of the ...

Effective Factors in the Survival Time of Covid-19 Patients in Three Epidemic Waves: A Prospective Cohort Study

Background and Objectives: This study aimed to investigate the effective factors in the survival/hazard time of Covid-19 patients in three waves of epidemic.   Methods: All 880 Covid-19 patients were included in this prospective cohort study using the census method. Polymerase chain reaction was used to diagnose Covid-19. The survival status of these patients was followed up for 4 months. The...

Comparison of Permutation Methods for the Partial Correlation and Partial Mantel Tests

This study compares empirical type I error and power of different permutation techniques that can be used for partial correlation analysis involving three data vectors and for partial Mantel tests. The partial Mantel test is a form of first-order partial correlation analysis involving three distance matrices which is widely used in such fields as population genetics, ecology, anthropology, psyc...

Mantel Permutation Tests

Covariate-adjusted nonparametric analysis of magnetic resonance images using Markov chain Monte Carlo.

Permutation tests are useful for drawing inferences from imaging data because of their flexibility and ability to capture features of the brain under minimal assumptions. However, most implementations of permutation tests ignore important confounding covariates. To employ covariate control in a nonparametric setting we have developed a Markov chain Monte Carlo (MCMC) algorithm for conditional p...