Continuous Trend Testing Versus Quantile Regression

Abstract

With linear trend testing of continuous data the outcome variable is continuous, the predictor variable is categorical, and can be measured either as nominal (just like names) or as ordinal variable (a stepping pattern not necessarily with equal intervals). In the Variable-View of SPSS the command “Measure” may, therefore, be changed into nominal or ordinal, but, since we assume an incremental function, the default measure “scale” is OK as well. The data example applied provided a p-value of 0.050 in the linear trend test. Better statistics can be obtained with the help of quantile regression, and, in addition, quantile regression tends to give a better overview of the relationships between predictor and outcome variables. In the example of this chapter quantile analysis not only better precision, but also better insight into the relationship between the predictor and outcome variable was obtained with p-values of 0.001 and 0.0001 rather than 0.050.

1 Supplementary Electronic Material (S)

chap6trendcontinuous (SAV 951 bytes)