Empirical Comparison of Tests for One-Factor ANOVA Under Heterogeneity and Non-Normality: A Monte Carlo Study

normality tests for statistical analysis: a guide for non-statisticians

statistical errors are common in scientific literature and about 50% of the published articles have at least one error. the assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends on it. the aim of this commentary is to overview checking for normality in statistical analysis using spss.

Comparison of TOF-PET and Bremsstrahlung SPECT images of Yttrium-90: A Monte Carlo Simulation Study

Objective(s): Yttrium-90 (90Y) is a beta particle nuclide used in targeted radionuclide therapy which is available to both single-photon emission computed tomography (SPECT) and time-of-flight (TOF) positron emission tomography (PET) imaging. The purpose of this study was to assess the image quality of PET and Bremsstrahlung SPECT by simulating PET and SPECT images of 90Y using Monte Carlo simu...

Residual-based tests for fractional cointegration: A Monte Carlo study

This paper reports on an extensive Monte Carlo study of seven residual-based tests of the hypothesis of no cointegration. Critical values and the power of the tests under the alternative of fractional cointegration are simulated and compared. It turns out that the Phillips-Perron t-test when applied to regression residuals is more powerful than Geweke-Porter-Hudak tests and the Augmented Dickey...

Asymptotic Normality in Monte Carlo Integration

To estimate a multiple integral of a function over the unit cube, Haber proposed two Monte Carlo estimators /'j and J'2 based on 2N and 4N observations, respec2 2 » tively, of the function. He also considered estimators Dy and D2 of the variances of/j and J'2, respectively. This paper shows that all these estimators are asymptotically normally distributed as N tends to infinity.

Comparison of One- and Two-day Protocols for Myocardial SPET: A Monte Carlo Study