Interrupted Time Series ARIMA (Intervention Analysis) - Advanced Tab

Select the Advanced tab of the Interrupted Time Series ARIMA dialog box to access the options described here.

Element Name Description
ARIMA model parameters Use the options in the ARIMA model parameters group box to select at least one seasonal or non-seasonal moving average or autoregressive parameter. If seasonal parameters are specified, a seasonal lag must also be specified.
Estimate constant Select the Estimate constant check box to include a constant in the ARIMA model. In addition to the autoregressive and moving average parameters, ARIMA models may also include a constant. The interpretation of a (statistically significant) constant depends on the model that is fit. Specifically, (1) if there are no autoregressive parameters in the model, then the expected value of the constant is μ, the mean of the series; (2) if there are autoregressive parameters in the series then the constant represents the intercept. If the series is differenced, then the constant represents the mean or intercept of the differenced series; For example, if the series is differenced once, and there are no autoregressive parameters in the model, then the constant represents the mean of the differenced series, and therefore the linear trend slope of the un-differenced series.
Seasonal lag Enter a value in the Seasonal lag box to determine the seasonal lag that is applied to the seasonal autoregressive and/or moving average parameters (option P-Seasonal and Q-Seasonal, respectively). Note that for very long seasonal lags (e.g., 365 days per year), it is recommended to use the Approximate rather than Exact maximum likelihood method, which is less efficient in those cases (see the Estimation method group box on the Options tab). Refer to the Overview for a discussion of the different methods for computing the likelihood for ARIMA models.
p - Autoregressive Enter a value in the p - Autoregressive box to specify the number of autoregressive parameters in the model.
P - Seasonal Enter a value in the P - Seasonal box to specify the number of seasonal autoregressive parameters in the model. If any seasonal parameters are selected, a Seasonal lag must also be specified.
q - Moving aver Enter a value in the q - Moving aver. box to specify the number of moving average parameters in the model.
Q - Seasonal Enter a value in the Q - Seasonal box to specify the number of seasonal moving average parameters in the model. If any seasonal parameters are selected, a Seasonal lag must also be specified.
Transform variable (series) prior to analysis The transformations selected via the Transform variable (series) prior to analysis group box are performed prior to the analysis, and the ARIMA parameters are estimated for the transformed series. Before forecasts are computed, those transformations will be "undone" and, therefore, those forecasts can be interpreted in terms of the metric of the untransformed series. Click the Other transformations & plots button (see below) to display the Transformations of Variables dialog box, which contains options for transformations that will not automatically be undone when forecasts are computed.
Natural log Select the Natural log check box to compute the natural log for each value.
Power transform When the Power transform check box is selected, each value in the series is raised to the power of C, where C is the value specified in the box adjacent to the Power transform check box.
Difference When the Difference check box is selected, the series is differenced. In keeping with the standard notation introduced by Box & Jenkins (1976), non-seasonal (1) and seasonal (2) differencing can be requested. Specify the respective Lag and the number of difference passes that are to be performed in the adjacent boxes.
Other transformations & plots Click the Other transformations & plots button to display the Transformations of Variables dialog box, which contains options to perform a wide variety of transformations on the data. The transformed series will be appended to the active work area.
Specify times and types of interventions The Specify time and type of interventions group box contains the options described here.
Intervention To specify an intervention, first select an Intervention check box. Up to 6 interventions can be specified.
At case number Enter the case number where the intervention occurred in the At case number box. Note that the case number should reference the actual case number in the file, not the offset (plus 1) from the first valid case. So for example, if the intervention occurs at case number 100 in the data file, but the first 20 cases of the series are missing, then you would still specify 100 as the time of intervention.
Type of intervention The Type of intervention menu contains three options. McDowall et. al (1980) distinguish among three major types of impacts that are possible: (1) Abrupt, Permanent, (2) Gradual, Permanent, and (3) Abrupt Temporary. For a description of these impacts, see impact patterns. These different impact patterns can also be reviewed (see the Review impact patterns tab).