Multi-sample inference for the simple-tree alternative based on one-sample confidence intervals

Abstract

The problem of testing homogeneity of several group means is considered against some patterned alternatives for the one-way classified data. The patterns of interest include the simple-tree and the trend alternatives. The approach is to begin with some suitably defined one-sample confidence intervals for the groups in a graphical display. Depending on the pattern of interest, orientation features of the display are examined, more formally, using proposed overall tests or rules. In the classical setup under normality, the case of known common variance is treated in detail; extensions to the case of unknown variance are indicated. When normality is in doubt, a nonparametric procedure based on the sign test is proposed. The necessary critical values are percentiles of either a multivariate normal distribution or a multivariate t-distribution. Although some existing tables can be used for the critical values (or the P-values) in some special cases, in general, the use of simulations is recommended and the steps are detailed in the appendix. An illustrative numerical example is provided.

Keywords:

• Simple-tree Alternative
• Trend Alternative
• Graphical Methods
• Isotonic Regression
• Nonparametric
• Confidence intervals
• Sign test