Statistical Methods for Hypothesis Testing

Dear Colleagues,

Researchers focus on answering questions through well-articulated hypotheses. Our ability to answer these questions influences the internal validity of results, meaning that we can attribute the change we see in the dependent variable on the independent variable and not another possible cause. Achieving this goal requires well-designed studies. Factors that influence internal validity include sampling and sample size, multiple testing, testing for assumptions, random assignment for experimental designs, and alpha selection, among others. Moreover, not every researcher subscribes to null hypothesis significance testing, further occluding this already difficult issue. The purpose of this Special Issue is, therefore, to assess the factors that influence the internal validity of studies. We are particularly interested in manuscripts that provide simulations that assess the impact of tested methods. Well-written manuscripts that aim to educate readers of all levels are particularly desired, as they will be critical to motivate researchers at all levels of statistical competence to pursue the research designs and analyses proposed. 

Prof. Dr. Daniel Rodriguez
Dr. Jamil Lane
Guest Editors

Manuscript Submission Information

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