Explorations in statistics: the analysis of change.

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This tenth installment of Explorations in Statistics explores the analysis of a potential change in some physiological response. As researchers, we often express absolute change as percent change so we can account for different initial values of the response. But this creates a problem: percent change is really just a ratio, and a ratio is infamous for its ability to mislead. This means we may fail to find a group difference that does exist, or we may find a group difference that does not exist. What kind of an approach to science is that? In contrast, analysis of covariance is versatile: it can accommodate an analysis of the relationship between absolute change and initial value when percent change is useless.

[1]  R. Fisher.  Statistical methods for research workers , 1927, Protoplasma.

[2]  Douglas Curran-Everett,et al.  Guidelines for reporting statistics in journals published by the American Physiological Society. , 2004, American journal of physiology. Endocrinology and metabolism.

[3]  Douglas Curran-Everett,et al.  Explorations in statistics: the bootstrap. , 2009, Advances in physiology education.

[4]  D. Curran‐Everett,et al.  Explorations in statistics: regression. , 2011, Advances in physiology education.

[5]  D. Altman,et al.  Analysing controlled trials with baseline and follow up measurements , 2001, BMJ : British Medical Journal.

[6]  V. Barnett,et al.  Applied Linear Statistical Models , 1975 .

[7]  D. Sengupta.  Linear models , 2003 .

[8]  Douglas Curran-Everett,et al.  Explorations in statistics: standard deviations and standard errors. , 2008, Advances in physiology education.

[9]  F. Yates,et al.  Statistical methods for research workers. 5th edition , 1935 .

[10]  Donald A. Berry,et al.  Statistical Methodology in the Pharmaceutical Sciences , 1989 .

[11]  Michael H. Kutner.  Applied Linear Statistical Models , 1974 .

[12]  R A FISHER,et al.  The analysis of covariance method for the relation between a part and the whole. , 1947, Biometrics.

[13]  Douglas Curran-Everett,et al.  Explorations in statistics: the analysis of ratios and normalized data. , 2013, Advances in physiology education.

[14]  Douglas Curran-Everett,et al.  Explorations in statistics: correlation. , 2010, Advances in physiology education.

[15]  Douglas Curran-Everett,et al.  Explorations in statistics: permutation methods. , 2012, Advances in physiology education.

[16]  Sanford Weisberg,et al.  An R Companion to Applied Regression , 2010 .

[17]  W. G. Cochran.  Analysis of covariance: Its nature and uses. , 1957 .

[18]  Nan M. Laird,et al.  Further Comparative Analyses of Pretest-Posttest Research Designs , 1983 .

[19]  D. Curran‐Everett,et al.  Explorations in statistics: hypothesis tests and P values. , 2009, Advances in physiology education.

[20]  D. Berry,et al.  Symmetrized Percent Change for Treatment Comparisons , 2006 .

[21]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[22]  John W. Tukey,et al.  Exploratory Data Analysis. , 1979 .

[23]  Walter T. Federer,et al.  Experimental Design, Theory and Application. , 1956 .

[24]  Handan Camdeviren Ankarali,et al.  Which Measure Should be Used for Testing in a Paired Design: Simple Difference, Percent Change, or Symmetrized Percent Change? , 2009, Commun. Stat. Simul. Comput..

[25]  Douglas Curran-Everett,et al.  Explorations in statistics: confidence intervals. , 2009, Advances in physiology education.

[26]  Andrew J Vickers,et al.  The use of percentage change from baseline as an outcome in a controlled trial is statistically inefficient: a simulation study , 2001, BMC medical research methodology.

[27]  D. Curran-Everett.  Explorations in statistics: power. , 2010, Advances in physiology education.

[28]  L Kaiser,et al.  Adjusting for baseline: change or percentage change? , 1989, Statistics in medicine.