We evaluated the impact of modelling intra-subject variability on the likelihood ratio test (LRT) and the Wald test based on non-linear mixed effects models in pharmacokinetic interaction and bioequivalence cross-over trials. These tests were previously found to achieve a good power but an inflated type I error when intra-subject variability was not taken into account. Trials were simulated und...

BACKGROUND We have observed that the area under the receiver operating characteristic curve (AUC) is increasingly being used to evaluate whether a novel predictor should be incorporated in a multivariable model to predict risk of disease. Frequently, investigators will approach the issue in two distinct stages: first, by testing whether the new predictor variable is significant in a multivariab...

This paper first establishes the asymptotic normality of plug-in sieve M estimators of possibly irregular functionals of semi-nonparametric time series models. We show that, even when the sieve score process is not a martingale difference, the asymptotic variances of plug-in sieve M estimators of irregular (i.e., slower than root-T estimable) functionals are the same as those for independent da...

This correspondence describes a new test for multivariate normality useful in pattern recognition. The test is based on the Friedman-Rafsky multivariate extension of the Wald-Wolfowitz runs test. We perform Monte-Carlo experiments to determine if the test is reliable in high dimensions with moderate sample size. We compare the test to some other tests mentioned in the literature.

An important issue for robust inference is to examine the stability of the asymptotic level and power of the test statistic in the presence of contaminated data. Most existing results are derived in finite-dimensional settings with some particular choices of loss functions. This paper re-examines this issue by allowing for a diverging number of parameters combined with a broader array of robust...

We develop a new asymptotic theory for autocorrelation robust tests using a vector autoregressive (VAR) covariance matrix estimator. In contrast to the conventional asymptotics where the VAR order goes to in…nity but at a slower rate than the sample size, we have the VAR order grow at the same rate, as a …xed fraction of the sample size. Under this …xed-smoothing asymptotic speci…cation, the as...

BACKGROUND The surge in biomarker development calls for research on statistical evaluation methodology to rigorously assess emerging biomarkers and classification models. Recently, several authors reported the puzzling observation that, in assessing the added value of new biomarkers to existing ones in a logistic regression model, statistical significance of new predictor variables does not nec...

This study primarily focuses on the analysis of contributions foreign exchange reserve to economic growth Nepal by using time series data obtained from year 1975 2018 A.D. In order assess a relationship between these variables, statistical procedure unit root test, cointegration and Vector Error Correction Model (VECM) are applied. addition t-statistics, Wald-test for joint significance coeffic...