You use factor weighting when you already know the weighting factor for the respondents in each population group on which you are basing your weighting. For example, you would use factor weighting when you are basing the weighting on gender and the weights have already been calculated as:

Similarly, you would use factor weighting when you are basing the weighting on characteristics recorded using two or more variables and the weight for each combination of categories has already been calculated. When using more than one variable, it is generally easiest to visualize this using a table. For example:

When you represent the weighting requirements in a table in this way, it is known as a weighting matrix.

When three variables are used, the third variable would form layers. Each layer is effectively a separate two-dimensional table filtered on a category of the variable that forms the layers. For example, suppose you want to use three variables--gender and age as in the previous example and the variable status, which has two categories Single and Has live-in partner. The first layer would define the weights for the respondents in the Single category and the second layer would define the weights for the respondents in the Has live-in partner category:

When you want to define factor and target weighting using three variables, you might sometimes find it easier to create a derived variable that combines the characteristics of two of the variables and use it in a two-dimensional weighting matrix rather than using a three-dimensional weighting matrix.