Testing non-additivity (interaction) in two-way ANOVA tables with no replication

Testing for any significant interaction between two variables depends on the number of replicates in each cell of the two-way table and structure of the interaction. If there is interaction between two factors model of observations include interaction term and is called ‘non-additive model’ which makes interaction and non-additivity equivalent in terms of meaning. When there are several observations taken at each level combination of two variables, testing non-additivity can easily be done by usual two-way ANOVA method which cannot be used when there is only one observation per cell. For the cases with only one observation per cell, some methods have been developed starting with Tukey’s one-degree-of-freedom test in which interaction is supposed to be the product of two factor’s effects. There are other methods which are used for different structures of interaction when there is only one observation. In this paper, we review some of these tests. After presenting general methodology for the two-factor linear model with interaction effect and the general two-way ANOVA method when there are n > 1 observations per cell, we present some methods for testing non-additivity when there is only one observation per cell. Finally, we illustrate these methods on examples.

[1]  William J. Glynn Asymptotic Distributions of Latent Roots in Canonical Correlation Analysis and in Discriminant Analysis with Applications, to Testing and Estimation. , 1977 .

[2]  Ronald D. Snee,et al.  Nonadditivity in a Two-Way Classification: Is it Interaction or Nonhomogeneous Variance? , 1982 .

[3]  K. Pillai,et al.  The distribution of the sphericity test criterion , 1973 .

[4]  J. Tukey One Degree of Freedom for Non-Additivity , 1949 .

[5]  N. Sugiura Locally Best Invariant Test for Sphericity and the Limiting Distributions , 1972 .

[6]  S. W. Cheng,et al.  Testing for interaction in two-way ANOVA tables with no replication , 1990 .

[7]  Matthias Egger,et al.  Insulin-like growth factor (IGF)-I, IGF binding protein-3, and cancer risk: systematic review and meta-regression analysis , 2004, The Lancet.

[8]  Y. Tunçok,et al.  The effects of propofol on normal and hypercholesterolemic isolated rabbit heart. , 2000, General pharmacology.

[9]  S. John Some optimal multivariate tests , 1971 .

[10]  John Mandel,et al.  Non-Additivity in Two-Way Analysis of Variance , 1961 .

[11]  Franklin A. Graybill,et al.  An Analysis of a Two-Way Model with Interaction and No Replication , 1972 .

[12]  J. Mandel A New Analysis of Variance Model for Non-additive Data , 1971 .

[13]  Robert J. Boik,et al.  Testing additivity in two-way classifications with no replications:the locally best invariant test , 1993 .

[14]  Franklin A. Graybill,et al.  Extensions of the General Linear Hypothesis Model , 1970 .

[15]  A comparison of three invariant tests of additivity in two-way classifications with no replications , 1993 .

[16]  James R. Matey,et al.  Evaluation and Control of Measurements , 1992 .

[17]  H. Freake,et al.  Actions and interactions of thyroid hormone and zinc status in growing rats. , 2001, The Journal of nutrition.