Defining repeat questions

There are a number of ways to handle repeated blocks of questions in QPSMR Companion. These methods are relevant whenever a respondent is asked the same set of questions for two or more products or situations. They may be used for small blocks of one or two questions, up to very large repeats making up the bulk of the questionnaire.

When deciding which method to use a primary consideration should be the accuracy of collecting the data. For this reason we recommend, whenever practicable, to enter the data directly from the questionnaires in the order which the questions appear on the printed document. We would particularly discourage any attempt to collate parts of individual questionnaires into some predefined order.

The descriptions which follow refer to a simple product test consisting of two repeats of two questions:

  • QA. What age are you? (Young, Old)
  • QP_1. Which product did you try first? (list of possible products)
  • QL_1. What did you like about the first product? (list of likes)
  • QR_1. Please rate the first product (Liked, Indifferent, Disliked)
  • QP_2. Which product did you try second? (list of possible products)
  • QL_2. What did you like about the second product? (list of likes)
  • QR_2. Please rate the second product (Liked, Indifferent, Disliked)
  • QP. Which did you prefer? (preferred first tested, preferred second tested, no preference)

To keep the analysis as simple as possible it is important that the responses for each repeated set of questions are exactly the same. So in our example, QP_1 has the same responses as QP_2, and QL_1 as QL_2 and QR_1 as QR_2. The entries QA and QP are only asked once.

We recommend using “similar” names for “similar” questions, as we have done above, rather than simply numbering them Q1 to Q8. It is much easier to produce the correct analysis when you use consistent numbering patterns from one repeat to the next.

One area of confusion that sometimes occurs when handling repeat questions is the base for individual tables. It is crucial that the person requesting a table, and the person producing it, both have a clear idea of the base for the table. In our example above we will assume that we have 100 respondents, who all try two products. We then have two possible bases for our tables:

Respondent based tables with a base of 100.

Product based tables with a base of 200 (less if not everyone tests two products).

It is possible to produce tables for all of the questions based on respondents (100) or products (200). If in doubt base the tables on products (200) using overlays or grid variables. Sometimes one base will make more sense than the other, and sometimes one base will be easier to produce, but there is neither a correct base nor an incorrect one, see Repeats overview.

Generally you will use the rows down the side of a table to determine the base.
For our survey, a typical respondent based table rows might be:

  • QA Age
  • VPROD Products tested
  • VPREF Preference

QP_1 and QP_2 cannot be used directly on respondent based tables because there are two of them for each respondent. Therefore it is necessary to make a multi variable (VPROD) using the block insert selection, which includes both questions combined with “or” so that each respondent will then have two products listed. Variable VPROD gives the answer to the (not asked) question “Which products did you try?”

You could create a variable from QL_1 and QL_2 in the same way, giving the likes for the respondent. This variable would answer the (not asked) question “What did you like about either or both of these products?”. This is not useful because you do not know which “likes” refer to which product. It would also be a mistake to tabulate this by VPROD on a respondent based table – the table you produce will be useless.

Tabulating QP directly in its current form also is not helpful, so a variable VPROD should be made with the responses “Preferred product A, Preferred product B, No preference”. If you are testing four products, but each respondent only tries two of them, VPROD will need four product preferred rows, plus a “No preference”. VPROD is not difficult to define – each row is taken in turn and defined from any of the relevant locations. For example “Preferred product A” is either “Preferred first” and A tried first, or “Preferred second” and A tried second. If A is QP_1/1 and QP_2/1 then the definition for “Preferred A” would be (QP_1/1 and QP/1) or (QP_2/1 and QP/2).

For our survey, typical product based tables might be:

  • Q1L + Q2L Likes
  • Q1R + Q2R Ratings

As we have seen above, making a respondent based variable for these questions is not helpful. To analyse these questions it is necessary to produce product based tables. This is done by producing two separate tables (one for first tried and one for second tried) and adding them together, using the overlay table facility. A typical table would be QL_1 by QP_1 and overlaid on it QL_2 by QP_2.

See also grid variables which automatically create overlaid tables when used.