ERIC Number: ED330708
Record Type: Non-Journal
Publication Date: 1991
Pages: 18
Abstractor: N/A
ISBN: N/A
ISSN: N/A
EISSN: N/A
Available Date: N/A
Graphical Description of Johnson-Neyman Outcomes for Linear and Quadratic Regression Surfaces.
Schafer, William D.; Wang, Yuh-Yin
A modification of the usual graphical representation of heterogeneous regressions is described that can aid in interpreting significant regions for linear or quadratic surfaces. The standard Johnson-Neyman graph is a bivariate plot with the criterion variable on the ordinate and the predictor variable on the abscissa. Regression surfaces are drawn for each group. If there are regions of significance, their boundaries are noted either on the graph or in the text. If there is a manageable number of cases, the cases may be plotted on the graph with different symbols for the groups. This standard style of representation often suffers from inclusion of too many cases for realistic plotting of data and from the difficulty in translating a bivariate display of data into univariate distributional characteristics of the two groups. The modification proposed here alleviates these problems. Computer programs for solutions in both linear and quadratic surfaces are included. These programs, which were written in GAUSS, differ from earlier programs in that the input required is summary information available from standard computer package output rather than raw data and is entered interactively. A 39-item list of references, three graphs, and seven pages of computer programming language are provided. (TJH)
Descriptors: Computer Software, Graphs, Interactive Video, Predictor Variables, Regression (Statistics)
Publication Type: Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A