Comparison of the Average Kappa Coefficients of Two Binary Diagnostic Tests with Missing Data

Article Mathematics

EM Algorithm for Mixture Distributions Model with Type-I Hybrid Censoring Scheme

Tzong-Ru Tsai et al.

Summary: An expectation-maximization (EM) likelihood estimation procedure is proposed for obtaining maximum likelihood estimates of parameters in a mixture distributions model with unknown mixture proportions based on type-I hybrid censored samples. Three bootstrap methods are utilized for constructing confidence intervals of the model parameters, and Monte Carlo simulations are conducted to evaluate the performance of the proposed methods. Simulation results demonstrate that the proposed methods can effectively provide reliable point and interval estimation results, with three examples illustrating their applications.

MATHEMATICS (2021)

Add to Collection

Article Mathematics

Global Hypothesis Test to Compare the Predictive Values of Diagnostic Tests Subject to a Case-Control Design

Saad Bouh Regad et al.

Summary: This manuscript explores the comparison of predictive values of two diagnostic tests in a case-control design, proposing a global hypothesis test for simultaneous comparison. Simulation experiments are conducted to study the performance of the hypothesis tests and the impact of prevalence misspecification on the asymptotic behavior of the tests and predictive value estimators. Additionally, the global hypothesis test is extended to situations with more than two diagnostic tests.

MATHEMATICS (2021)

Add to Collection

Article Mathematics

An Alternative Promotion Time Cure Model with Overdispersed Number of Competing Causes: An Application to Melanoma Data

Diego Gallardo et al.

Summary: A cure rate model under the competing risks setup was proposed in this study, with parameter estimation based on maximum likelihood method and estimates computed via the EM algorithm. A selection criterion for non-nested models was implemented to compare different models. Simulation studies and analysis of real data on melanoma indicated good performance of the estimation method and model selection criterion.

MATHEMATICS (2021)

Add to Collection

Article Mathematics

Estimation of the Average Kappa Coefficient of a Binary Diagnostic Test in the Presence of Partial Verification

Jose Antonio Roldan-Nofuentes et al.

Summary: This study investigated the estimation of the average kappa coefficient of a diagnostic test in the presence of verification bias, comparing the methods of maximum likelihood and multiple imputation. Simulation experiments showed that multiple imputation by chained equations method yielded better results than the maximum likelihood method, with implications for the diagnosis of liver disease.

MATHEMATICS (2021)

Add to Collection

Article Mathematics

Confidence Intervals and Sample Size to Compare the Predictive Values of Two Diagnostic Tests

Jose Antonio Roldan-Nofuentes et al.

Summary: This manuscript focuses on comparing the positive (negative) predictive values of two binary diagnostic tests through confidence intervals in a paired design. Simulation experiments have been conducted to study the behavior of the confidence intervals asymptotically, providing general rules for application. The manuscript also discusses a method for calculating sample size for comparing parameters using confidence intervals, with results applied to the diagnosis of colorectal cancer.

MATHEMATICS (2021)

Add to Collection

Article Computer Science, Interdisciplinary Applications