Use and misuse of multiple comparisons in animal experiments.

The objective of many animal experiments is to detect meaningful relationships among treatments and associated responses. Types of comparisons of means include pairwise multiple comparisons, planned orthogonal or nonorthogonal contrasts, and orthogonal polynomials. Some procedures are appropriate only for specific types of treatment designs and specific types of objectives. Pairwise, multiple comparisons are appropriate only for comparing unstructured, qualitative treatments. Planned comparisons partition the overall set of treatment effects into independent or nonindependent subsets, with special application to factorials. Orthogonal polynomial (regression) procedures assess relationships between quantitative treatments and response when a full range of responses or an optimal dose is of interest. Recommendations for appropriate use of each mean comparison procedure are illustrated using data from three Journal of Animal Science articles. Also mentioned are a number of computer graphics packages that provide creative ways to display biological relationships and can be linked to statistical packages for input and to word processors or 35-mm cameras for output.

[1]  E. Lehmann,et al.  On a Fundamental Theorem in Multiple Comparisons , 1977 .

[2]  J. Perry,et al.  Multiple-comparison procedures: a dissenting view. , 1986, Journal of economic entomology.

[3]  D. B. Duncan.  MULTIPLE RANGE AND MULTIPLE F TESTS , 1955 .

[4]  S. G. Carmer,et al.  Baby Bear's Dilemma: A Statistical Tale1 , 1982 .

[5]  James H. Torrie,et al.  Principles and procedures of statistics: a biometrical approach (2nd ed) , 1980 .

[6]  D. Saville.  Multiple Comparison Procedures: The Practical Solution , 1990 .

[7]  C. Dunnett.  A Multiple Comparison Procedure for Comparing Several Treatments with a Control , 1955 .

[8]  H. Dawkins.  Multiple Comparisons Misused: Why so Frequently in Response-Curve Studies? , 1983 .

[9]  R. G. Petersen.  Use and Misuse of Multiple Comparison Procedures1 , 1977 .

[10]  P. Cornelius,et al.  Analyzing Herbicide Interactions: A Statistical Treatment of Colby's Method , 1988, Weed Technology.

[11]  D. Jones,et al.  Use, Misuse, and Role of Multiple-Comparison Procedures in Ecological and Agricultural Entomology , 1984 .

[12]  Mervyn G. Marasinghe,et al.  SAS System for Linear Models , 1991 .

[13]  R. Schultz,et al.  Comparing treatment means correctly and appropriately , 1985 .

[14]  Kathy Shelley.  EVALUATION OF PRESENTATION GRAPHICS FOR THE AGRICULTURAL SCIENCES , 1989 .

[15]  Charles W. Dunnett,et al.  New tables for multiple comparisons with a control. , 1964 .

[16]  M. O'Mahony.  Sensory Evaluation of Food: Statistical Methods and Procedures , 1986 .

[17]  O'Brien Pc,et al.  The appropriateness of analysis of variance and multiple-comparison procedures. , 1983 .

[18]  S. G. Carmer,et al.  An Evaluation of Ten Pairwise Multiple Comparison Procedures by Monte Carlo Methods , 1973 .

[19]  William G. Hunter.  The Practice of Statistics: The Real World is an Idea Whose Time Has Come , 1981 .

[20]  J. L. Gill.  Current Status of Multiple Comparisons of Means in Designed Experiments , 1973 .

[21]  S. G. Carmer.  Optimal Significance Levels for Application of the Least Significant Difference in Crop Performance Trials1 , 1976 .

[22]  Charles W. Dunnett,et al.  Multiple Comparisons for Orthogonal Contrasts: Examples and Tables , 1982 .

[23]  R. A. Waller,et al.  A Bayes Rule for the Symmetric Multiple Comparisons Problem , 1969 .

[24]  Wendell C. Smith,et al.  Error rate for testing a contrast after a significant F test , 1981 .

[25]  R Mead,et al.  A review of response surface methodology from a biometric viewpoint. , 1975, Biometrics.