Experimental Design and Data Analysis of In Vivo Fluorescence Imaging Studies.

The objective of this chapter is to provide researchers who conduct in vivo fluorescence imaging studies with guidance in statistical aspects in the experimental design and data analysis of such studies. In the first half of this chapter, we introduce the key statistical components for designing a sound in vivo experiment. Particular emphasis is placed on the issues and designs that pertain to fluorescence imaging studies. Examples representing several popular types of fluorescence imaging experiments are provided as case studies to demonstrate how to appropriately design such studies. In the second half of this chapter, we explain the fundamental statistical concepts and methods used in the data analysis of typical in vivo experiments. We also provide specific examples in in vivo imaging studies to illustrate the key steps of analysis procedure.

[1]  John J. Hanfelt,et al.  Statistical approaches to experimental design and data analysis of in vivo studies , 1997, Breast Cancer Research and Treatment.

[2]  Helen Brown,et al.  Applied Mixed Models in Medicine , 2000, Technometrics.

[3]  A. Agresti.  An introduction to categorical data analysis , 1997 .

[4]  H. B. Mann,et al.  On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .

[5]  W. Russell,et al.  Ethical and Scientific Considerations Regarding Animal Testing and Research , 2011, PloS one.

[6]  K. Pearson.  On the Criterion that a Given System of Deviations from the Probable in the Case of a Correlated System of Variables is Such that it Can be Reasonably Supposed to have Arisen from Random Sampling , 1900 .

[7]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[8]  Karl Pearson F.R.S..  X. On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling , 2009 .

[9]  Douglas G Altman,et al.  Guidelines for the design and statistical analysis of experiments using laboratory animals. , 2002, ILAR journal.

[10]  W. Kruskal,et al.  Use of Ranks in One-Criterion Variance Analysis , 1952 .

[11]  J. Reid.  Experimental Design and Data Analysis for Biologists , 2003 .

[12]  Margaret J. Robertson,et al.  Design and Analysis of Experiments , 2006, Handbook of statistics.

[13]  R A Fisher.  The causes of human variability. , 2016, International journal of epidemiology.

[14]  Robin J. Prescott,et al.  Applied Mixed Models in Medicine: Brown/Applied Mixed Models in Medicine, 2nd Edition , 2006 .

[15]  Simon T. Bate,et al.  The Design and Statistical Analysis of Animal Experiments , 2014 .

[16]  F. Wilcoxon.  Individual Comparisons by Ranking Methods , 1945 .