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RIM weighting

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RIM weighting uses a mathematical algorithm to help you provide an even distribution of results across the entire dataset while balancing certain categories such as age or gender to pre-determined totals. It weights the specified characteristics simultaneously and disturbs each variable as little as possible.

RIM weighting is used when you wish to provide weighting for more than one variable. It can also be used to produce an analysis in which the proportion of respondents in your sample are adjusted to match more closely to the proportion in the target population.

For example, if you wished to weight your samples so that they were 50% male and 50% female, and also 20% in each of five age brackets, the algorithm would calculate the correct weighting that needed to be applied to each table entry (combining age and gender).

RIM weighting works best for single response variables where there is no missing data, and the counts or percentages are similar to the existing data responses.

It is not a good idea to use rim-weighting if:

  • Your variables are related to each other (for example, income bracket and dwelling size).
  • The values vary enormously (for example, you have 96 males and four females, and you are attempting to balance it to 50:50).
  • You are applying a very large number of weights.

Creating a RIM Weight

  1. In the Survey Overview window, open the survey.
  2. Click Analysis Variables on the Snap Desktop toolbar. This opens the Analysis Variables window which displays a list of the analysis variables.
  3. Click New Analysis Variables Item on the Analysis Variables toolbar. This displays a menu of analysis variables to choose from.
  4. Click New RIM Weight. This opens the RIM Weight window. Note that initially an error is shown in the status bar as there are no variables selected yet.
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  1. In Name, enter the name that will be used to identify the RIM weight.
  2. In Label, enter a description of the RIM weight.
  3. In Target total, select the required option. There are three options for setting the Target total: Valid cases, From targets and Custom. Note: The RIM weighting in Snap Desktop works out whether the number entered in Ratio is a percentage, proportion or target number and does not require a percentage sign (%) to be entered.

Valid cases bases the RIM weight on the valid data responses in the survey. The default ratio is 1 to give an equal distribution for all variable codes. The Ratio column can be changed with a proportion or target number for each variable code. For a target number to be used the total numbers in the Ratio column (per variable) must add up to the number of valid cases, otherwise a proportional ratio is used. The Expected column shows the target counts. The total number of valid cases is shown next to the drop-down.

RIM weight with Valid cases selected and an equal ratio distribution

From targets allows a ratio or target number to be set for each code within a variable. This is set in the Ratio column. The target number is shown next to the drop down and is the count of the target number for each variable code entered in the Ratio column. The Expected column shows the target counts for each variable code.

RIM weight with From targets selected and target numbers set for each code

Custom allows an overall target number to be entered. Selecting this option enables the field next to the drop-down where you can enter the target number. The default ratio is 1 which shows an equal distribution of the target number split across all the codes within each variable. The target number can be edited in the Ratio column. The Expected column shows the target counts for each variable code.

RIM weight with Custom selected and target numbers set for each code
  1. In Missing data, choose whether partial cases should be included or excluded. Excluding the partial cases provides the most accurate result as the partial cases have missing data in their responses. By default, this is set to exclude partial cases.
  2. In Filter, enter a filter expression to create the RIM weight for a subset of the response data.
  3. Click Add Variable to select a variable. When the variable is added the default values for the RIM weight are set up in the grid. The grid of variables shows the ratio, expected count and percentage as well as the actual count and percentage.
  4. Click in the Ratio column to change the ratio or target number depending on the Target total option selected.
  5. Repeat for all the variables you wish to add. Click Delete Variable to delete the selected variable from the RIM Weight.
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  1. Click Save to save the RIM weight.

Tailor the RIM Weight

You can customise the decimal places, maximum iterations and match threshold for the RIM weighting.

  • Click Tailor on the RIM Weight toolbar to enter the settings and click OK to save.

Assess the RIM Weight

Assessing the RIM Weight gives statistics of how efficiently the RIM weight will meet the target.

  1. Click Assess RIM Weight on the RIM Weight toolbar to assess the RIM weight.
  2. A summary is shown with the build information. Click OK to close the summary.

If there is an error in the RIM weight the status bar will show an error message and clicking Assess RIM Weight will also show an error message.

Build the RIM Weight

The status of the RIM Weight is shown in the status bar at the bottom of the RIM Weight window. When the RIM Weight is created the status shows as Not built.

  1. Click Build RIM Weight on the RIM Weight toolbar to build the RIM weight.
  2. The Status changes to show Built. If there is an error in the RIM weight the status bar will show an error message and the RIM weight is not built.
  3. Click Save to save the RIM weight.

Using the RIM Weight

The RIM weight can be included when creating analyses.

  1. Click the required analysis icon on the Snap Desktop toolbar. This opens the Analysis Definition window.
  2. In Analysis and Break, enter appropriate break and analysis fields.
  3. In Weight, enter the name of the RIM weight.
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  1. Click OK to build the rim-weighted analysis.
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