An empirical study using permutation-based resampling in meta-regression

An empirical study using permutation-based resampling in meta-regression

BACKGROUND In meta-regression, as the number of trials in the analyses decreases, the risk of false positives or false negatives increases. This is partly due to the assumption of normality that may not hold in small samples. Creation of a distribution from the observed trials using permutation methods to calculate P values may allow for less spurious findings. Permutation has not been empirica...

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Resampling Based Empirical Prediction: An Application to Small Area Estimation

Best linear unbiased prediction is well known for its wide range of applications including small area estimation. While the theory is well established for mixed linear models and under normality of the error and mixing distributions, the literature is sparse for nonlinear mixed models under nonnormality of the error or of the mixing distributions. This article develops a resampling based unifie...

Empirical Study of Population Diversity in Permutation-Based Genetic Algorithm

This paper presents an empirical study of population diversity measure and adaptive control of diversity in the context of a permutation-based algorithm for Traveling Salesman Problems and Vehicle Routing Problems. Maintenance of diversity adaptive control is one of the most fundamental issues of Genetic Algorithm (GA). We are concerned in this paper with GA in which individual chromosomes are ...

Regression Based Test Case Selection: An Empirical Study

Test case selection techniques schedule test cases for execution in an order that attempts to maximize some objective function. Regression testing is a maintenance activity that is performed to ensure the validity of modified software. The activity takes a lot of time to run the entire test suite and is very expensive. Thus it becomes a necessity to choose the minimum set of test cases with the...