# Ordinal Regression using SPSS Statistics (cont...)

## Procedure II – Running the PLUM Procedure

The instructions below show you how to run the PLUM procedure. Some of this will require using syntax, but we explain what you need to do. This step produces some of the main results for your ordinal regression analysis, including predicted probabilities, amongst other useful statistical measures we discuss in the Interpretation and Reporting section later.

- Click
on the main menu, as shown below:__A__nalyze >__R__egression > Or__d__inal...Published with written permission from SPSS Statistics, IBM Corporation.

You will be presented with the**Ordinal Regression**dialogue box, as shown below:

Published with written permission from SPSS Statistics, IBM Corporation.

- Transfer the ordinal dependent variable – tax_too_high – into the
__D__ependent: box. Next, transfer the categorical independent variables – biz_owner and politics – into the__F__actor(s) box and the continuous independent variable – age – into the__C__ovariate(s) box, using the appropriate buttons. You will end up with a screen similar to that below:Published with written permission from SPSS Statistics, IBM Corporation.

Explanation: Ordinal regression can accept independent variables that are either nominal, ordinal or continuous, although ordinal independent variables need to be treated as either nominal or continuous variables. In the

**Ordinal Regression**dialogue box, independent nominal variables are transferred into the__F__actor(s) box and independent continuous variables are transferred into the__C__ovariate(s) box. You can transfer an ordinal independent variable into either the__F__actor(s) or__C__ovariate(s) box depending on how you wish the ordinal variable to be treated. However, this is a decision that you need to make. - Click on the button and you will be presented with the
**Ordinal Regression: Options**dialogue box, as shown below:Published with written permission from SPSS Statistics, IBM Corporation.

Note: It is unlikely that you will need to change any of the options in the

**Ordinal Regression: Options**dialogue box shown above. Indeed, in this example you will not change anything. However, if you wanted to change the confidence intervals (the__C__onfidence interval: box) from 95% or change the type of link function (the Lin__k__: drop-down box) used, you could do that here. - Click on the button and you will be returned to the
**Ordinal Regression**dialogue box. - Click on the button and you will be presented with the
**Ordinal Regression: Output**dialogue box, as shown below:Published with written permission from SPSS Statistics, IBM Corporation.

- In addition to the options already selected, select Test of para
__l__lel lines in the –Display– area. Also, in the –Saved Variables– area, select all four options:__E__stimated response probabilities, Pre__d__icted category, Predicted category pro__b__ability and__A__ctual category probability. You will end up with a screen similar to below:Published with written permission from SPSS Statistics, IBM Corporation.

Note 1: When you only have categorical independent variables, you may also want to select Cell informa

__t__ion. However, as a general rule, the Cell informa__t__ion option is not very useful when you have continuous independent variables in the model (as in this example).Note 2: Keeping the default I

__n__cluding multinomial constant option selected in the –Print Log-Likelihood– area results in the FULL log-likelihood being produced, whereas the E__x__cluding multinomial constant option results in the KERNAL of the log-likelihood being produced. This affects the value of the log-likelihood, but not the conclusion. This is explained in our enhanced ordinal regression guide if you are unsure. - Click on the button and you will be returned to the
**Ordinal Regression**dialogue box.