1,720,979 research outputs found
SASWeave: Literate Programming Using SAS
Get PDFSASweave is a collection of scripts that allow one to embed SAS code into a LATEX document, and automatically incorporate the results as well. SASweave is patterned after Sweave, which does the same thing for code written in R. In fact, a document may contain both SAS and R code. Besides the convenience of being able to easily incorporate SAS examples in a document, SASweave facilitates the concept of "literate programming": having code, documentation, and results packaged together. Among other things, this helps to ensure that the SAS output in the document is in concordance with the code.
Response-Surface Methods in R, Using rsm
Get PDFThis article describes the recent package rsm, which was designed to provide R support for standard response-surface methods. Functions are provided to generate central-composite and Box-Behnken designs. For analysis of the resulting data, the package provides for estimating the response surface, testing its lack of fit, displaying an ensemble of contour plots of the fitted surface, and doing follow-up analyses such as steepest ascent, canonical analysis, and ridge analysis. It also implements a coded-data structure to aid in this essential aspect of the methodology. The functions are designed in hopes of providing an intuitive and effective user interface. Potential exists for expanding the package in a variety of ways.
Power Analysis for Experimental Research: A Practical Guide For The Biological, Medical and Social Sciences. R. Barker Bausell and Yu-fang Li & Statistical Power Analysis: A Simple and General Model for Traditional and Modern Hypothesis Tests (2nd Ed.). Kevin R. Murphy and Brett Myors
No full textPost Hoc Power: Tables and Commentary
No full textPost hoc power is the retrospective power of an observed effect based on the sample size and parameter estimates derived from a given data set. Many scientists recommend using post hoc power as a follow-up analysis, especially if a finding is nonsignificant. This article presents tables of post hoc power for common t and F tests. These tables make it explicitly clear that for a given significance level, post hoc power depends only on the P value and the degrees of freedom. It is hoped that this article will lead to greater understanding of what post hoc power is—and is not. We also present a “grand unified formula ” for post hoc power based on a reformulation of the problem, and a discussion of alternative views. Key words: Post hoc power, Observed power, P value, Grand unified formula
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