Nonparametric linear tests with multiple events
Computational Statistics & Data Analysis
A nonparametric test for the equality of counting processes with panel count data
Computational Statistics & Data Analysis
Computational Statistics & Data Analysis
On power and sample size computation for multiple testing procedures
Computational Statistics & Data Analysis
Semiparametric regression analysis of panel count data with informative observation times
Computational Statistics & Data Analysis
Joint estimation of mean-covariance model for longitudinal data with basis function approximations
Computational Statistics & Data Analysis
One-sided multiple comparisons for treatment means with a control mean
Computational Statistics & Data Analysis
Quantile regression for longitudinal data with a working correlation model
Computational Statistics & Data Analysis
A semiparametric Bayesian approach to generalized partial linear mixed models for longitudinal data
Computational Statistics & Data Analysis
Robust estimation for panel count data with informative observation times
Computational Statistics & Data Analysis
Modeling time-dependent overdispersion in longitudinal count data
Computational Statistics & Data Analysis
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Nonparametric comparison for panel count data is discussed. For the situation, most available approaches require that all subjects have the same observation process. However, such an assumption may not hold in reality. To address this, a new class of test procedures are proposed that allow unequal observation processes for the subjects from different treatment groups. The method applies to both univariate and multivariate panel count data. In addition, the asymptotic normality of the proposed test statistics is established and a simulation study is conducted to evaluate the finite sample properties of the proposed approach. The simulation results show that the proposed procedures work well for practical situations and in particular for sparsely distributed data. They are applied to a set of panel count data arising from a skin cancer study.