Log In/Create Account

My results in R-DAS were blocked by the disclosure protection settings. How do I avoid having my output blocked?

Because of confidentiality concerns, we are unable to provide specific details about what is causing the disclosure protection settings to block output for a specific analytic run. However, we are able to provide solutions for several common reasons that analytic results are blocked.

When output is blocked, you may get one these messages:

Definitions of the various blocked result messages are available in another FAQ.

Below are several examples of analytic requests where the results were blocked, and possible solutions for how to change your request to receive some analytic results.

Example 1: A user runs a crosstabulation where State is the column variable.

Possible solutions:

If interested in a single state, you might try placing the State variable in the Filter field to specify the one state for analysis. For example, entering STATE(1) in the filter field will give you results for just Alabama. Focusing your analysis on only one state might help you avoid a circumstance where a different state is causing your results to be blocked.

Another option would be to use a geographic variable like Census Region or Division in an attempt to avoid low record counts that can result in causing your results to be blocked.

Example 2: A user runs a crosstabulation where AGE is the column variable.

Possible Solutions:

The AGE variable spans an age range from 12 to 103 years old. You could try using one of the categorized age variables within the data file.

Alternatively, you could utilize the temporary recode feature in R-DAS that allows you to recode a variable into fewer categories.

Help documentation on doing temporary recodes can be found at: http://www.icpsr.umich.edu/icpsrweb/content/SAMHDA/help/helpan.htm#recode

Example 3: A user runs a three-way crosstabulation using the Row, Column, and Control fields. However, the results are blocked, and the user has no idea which variable or combination of variables contains the low record count.

Possible solutions:

Run frequencies for the variables in your analysis one at a time. One variable may stand out as having a value with a particularly low weighted frequency. It is possible that a variable has a value with such a small record count that the univariate frequency is blocked. If one variable does stand out as being the primary cause of the problem, then you could check to see if a similar variable exists with fewer categories, or you could do a temporary recode to create larger record counts.

If no single variable stands out as causing the problem, then try running crosstabs on two of your variables. If any cross combination of values from the two variables has a particularly low weighted frequency, then this can be an indicator that the combination is the cause of the problem. If one combination does stand out, you could find similar variables to the ones you chose, but have fewer categories. Again, you could do a temporary recode on one or more of your variables to create larger record counts for the categories/values of the two variables that are the possible cause of the problem.