We first examine the simple linear regression model for satisfaction using patient age as the sole predictor, i.e. We can see both age and severity of illness are negatively correlated with the response satisfaction, and are positively correlated with each other as would be expected. I have added the following options to the display: Show Correlations and Horizontal from the Show Histograms option. The scatterplot matrix for these variables is shown on the next page. The diagonals are all 1.000 because the correlation of any variable with itself is 1. It gives all pairwise correlations between these variables.
The output below gives a correlation matrix for Age, Severity, and Satisfaction. To do this in JMP select Analyze > Multivariate Methods > Multivariate as shown below. 79 – 83) HospSatisfaction (Table 3.2).JMP Before fitting any regression model it is good idea to plot the response variable and the potential predictors in a scatterplot matrix. – Regression Analysis – Computing in JMP Example 1: Patient Satisfaction Survey (pgs.
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