Revisiting the Assumptions for Inferential Statistical Analyses: A Conceptual Guide

Assumptions for Statistical Inference

In this paper we overview and discuss some of the important practical assumptions underlying statistical inference. What we say, though not new, is stressed insu ciently in teaching statistical methods and applications. We build on the important conceptual di erence between enumerative and analytic studies, emphasized by W. Edwards Deming. Our comments, however, go beyond the published views of...

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.

Ingredients for change: revisiting a conceptual framework.

Finding ways to deliver care based on the best possible evidence remains an ongoing challenge. Further theoretical developments of a conceptual framework are presented which influence the uptake of evidence into practice. A concept analysis has been conducted on the key elements of the framework--evidence, context, and facilitation--leading to refinement of the framework. While these three esse...

Guide to the use of statistical methods in clinical studies

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Statistical Models for Causation : What Inferential Leverage