When configuring an analysis, you can use Advanced Settings to further fine-tune Sisu’s analysis and output.

**Related Articles:**

- Configuring a General Performance Analysis
- Configuring a Time Comparison Analysis
- Configuring a Group Comparison Analysis

## Using Advanced Settings to Fine-Tune an Analysis

- Access the Analysis, then click the
**Top Drivers Settings**button icon to access advanced settings. - Adjust Sisu’s sensitivity settings in finding facts as desired.

**Statistical Model Settings**Select the type of statistical model you would like Sisu to use to determine top drivers in the Analysis. Depending on the kind of analysis and metric you are diagnosing, you will have up to three choices:

- Top Drivers (Higher accuracy model)
- Top Drivers (Original model)
- All subgroups

Refer to Understanding Statistical Models for a description of each model.

**Confidence Level**Generally speaking, Sisu tests for statistical significance for all the Subgroups within the data set and only surfaces ones that pass the test. By default, the confidence level is set at 95% .

If you do not see sufficient facts in the results, this may be because:

- Your Metric did not change significantly and so no factors in your data explain it
- Your Metric did change, but the factors do not explain why
- You have a smaller data set (<1,000 Rows)

In these cases you may lower the confidence level to see if you get more facts (but at a lower confidence). Refer to Understanding Statistical Models for more details on how this is determined for different types of Analysis.

**Subgroup settings: Minimum subgroup size**This is the minimum size (percentage of rows) that a subgroup must have for it to show up as a fact.

- For example, if there are 100,000 rows in the data set, a subgroup will appear as a fact only if it contains at least 100 rows (0.1% of 100,000 rows).
- For small data sets in particular (less than 10k rows), reducing this setting can help make more facts appear in the analysis result.

**Maximum subgroup order**Sisu explores all possible combinations of your data columns and identifies top subgroups that have high impact on your metric.

- When we explore one column, then it's “Order 1” fact (e.g., country = Canada).
- When we explore a combination of two columns, then it's “Order 2” fact (e.g., country = Canada & gender = F).
- When we explore a combination of two columns, then it's “Order 2” fact (e.g.,country = Canada, gender = F, and age > 18).

The default settings is 3. You may want to decrease this for faster analysis.

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