Complex Samples Ordinal Regression Options
Estimation Method. You can select a parameter estimation method; choose between Newton-Raphson, Fisher scoring, or a hybrid method in which Fisher scoring iterations are performed before switching to the Newton-Raphson method. If convergence is achieved during the Fisher scoring phase of the hybrid method before the maximum number of Fisher iterations is reached, the algorithm continues with the Newton-Raphson method.
Estimation. This group gives you control of various criteria used in the model estimation.
- Maximum Iterations. The maximum number of iterations the algorithm will execute. Specify a non-negative integer.
- Maximum Step-Halving. At each iteration, the step size is reduced by a factor of 0.5 until the log-likelihood increases or maximum step-halving is reached. Specify a positive integer.
- Limit iterations based on change in parameter estimates. When selected, the algorithm stops after an iteration in which the absolute or relative change in the parameter estimates is less than the value specified, which must be non-negative.
- Limit iterations based on change in log-likelihood. When selected, the algorithm stops after an iteration in which the absolute or relative change in the log-likelihood function is less than the value specified, which must be non-negative.
- Check for complete separation of data points. When selected, the algorithm performs tests to ensure that the parameter estimates have unique values. Separation occurs when the procedure can produce a model that correctly classifies every case.
- Display iteration history. Displays parameter estimates and statistics at every n iterations beginning with the 0th iteration (the initial estimates). If you choose to print the iteration history, the last iteration is always printed regardless of the value of n.
User-Missing Values. Scale design variables, as well as the dependent variable and any covariates, should have valid data. Cases with invalid data for any of these variables are deleted from the analysis. These controls allow you to decide whether user-missing values are treated as valid among the strata, cluster, subpopulation, and factor variables.
Confidence Interval. This is the confidence interval level for coefficient estimates, exponentiated coefficient estimates, and odds ratios. Specify a value greater than or equal to 50 and less than 100.
How To Specify Options for Complex Samples Ordinal Regression
This feature requires the Complex Samples option.
- From the
menus choose:
- Select a plan file. Optionally select a custom joint probabilities file.
- Click Continue.
- In the Complex Samples Ordinal Regression dialog box, click Options.
- Select the options you want.