The Ipsative Process to Reduce Response Set Bias

Researchers who gather data from several different groups are frequently faced with the problem of response set bias. This paper discusses the ipsative process, a technique which can reduce systematic response bias which exists between groups in a study. The usefulness of the ipsative process is illustrated on cross-cultural research findings gathered in four countries. William H. Cunningham is Associate Professor of Marketing Administration, Isabella C. M. Cunningham is Associate Professor of Advertising, and Robert T. Green is Associate Professor of Marketing Administration, at the University of Texas at Austin. The authors would like to thank Professor Donald J. Veldman of the University of Texas at Austin for his help with this research. POQ 41 (1977) 379-384 This content downloaded from 157.55.39.246 on Tue, 27 Sep 2016 04:53:58 UTC All use subject to http://about.jstor.org/terms 380 CUNNINGHAM, ET AL. The Ipsative Measure When data are ipsatized, an individual's score on each variable is dependent on his score on the other variables. The mathematical definition of ipsative data is: "Any score matrix, which has the property that the sum of the scores over the attributes for each of the entities is a constant" (Clemans, 1956). Any data matrix may be made ipsative by adding the appropriate value to each subject's responses such that all of the subject's scores will sum to the same number. This key value is determined by summing the scores in the row and then subtracting a constant from the sum of the variables and dividing the remainder by the number of variables. As an example, assume that an individual had scores on three variables of 75, 35, and 85. To ipsatize these data the scores would first be summed to 195. A constant, for example 100, is subtracted from 195 and the remainder is divided by 3. As a result 31.7 is subtracted from each of the original scores on the three variables. The subject's ipsatized values would therefore equal 43.3, 3.3, and 53.3. To ipsatize an entire primary data matrix this procedure would be followed for each individual in the sample. In order for the ipsative process to be meaningful, however, the researcher must standardize the data both before and after ipsatizing. Thus, the entire process would involve three steps. First, the primary data matrix must be standardized by columns to force each variable to a common base. As a result, each variable may be compared with every other variable without any bias that would arise from variations in the means and standard deviations of the variable. Second, the standard score matrix is ipsatized in the manner presented above. At this point, the ipsative scores make it possible to compare an individual's relative score on each variable with his score on other variables. Finally, if the objective of research is to compare one individual with another or two sets of individuals with each other, the ipsative scores must be transformed into standard scores by columns. Since the usual objective of the ipsative process is to be able to compare groups of individuals across a set of variables, this final data manipulation is normally needed (Clemans, 1956:5-7).