Scaling involves assigning numbers to objects in accordance with a specific rule. The objects include text statements—normally statements that tell about respondents’ attitudes or opinions. Scaling is different from a response scale in one distinct way. Scaling is a process that entails the assigning of values to variables whereas a response scale is an instrument used to give values to responses collected from respondents (Creswell, 2009). An example of a response scale is a dichotomous scale that has agree/disagree options or an interval scale that has options ranging from 0 to 5. In both scales, the respondent chooses the option which best suits his or her response to the question asked by the researcher. Scaling entails the entire process of developing the response scales that best suit the questions that will be asked as well as the methods that will be used to analyze the values provided in the response scales (Trochim and Donnelly, 2008).
It is important to note that even though a scale is a tool that can be used independently, it is usually incorporated into a bigger and composite instrument, for instance, a survey. The majority of the surveys are created to evaluate numerous issues of interest and to gather the information that makes it possible for the researcher to identify the correlations between such issues. When the information is gathered, the scores of the different scales used in the survey are computed and inferences are then made from the data analysis.
In research, scaling is done for a number of reasons. The first reason is to test the hypotheses of the study. The researcher carries out scaling so as to know which variables are best constructed as one-dimensional and multi-dimensional. A one-dimensional variable is one that carries only one score. Examples of one-dimensional variables include height, weight, and age. Examples of multi-dimensional variables include intelligence which can be measured using mathematical and verbal skills. The second reason for conducting scaling is that it enables the researcher to identify what dimensions are best suited to a range of ratings. For example, if a researcher develops a range of queries for his/her study, he/she can use scaling to know how suitable the questions are to the study’s objectives and if the questions can measure one variable or multiple variables. The third reason for scaling is to represent a response using a single value. When a respondent responds to a range of questions, the researcher can assign a single value that best represents the respondent’s general opinion and mindset (Trochim and Donnelly, 2008).
Scales are commonly used with complex variables that cannot be easily measured using a single score or single indicator. These variables include mostly qualitative variables. Quantitative variables such as the age of the respondent and the number of children of the respondent can easily be measured without the use of a scale. However, qualitative variables such as a participant’s belief concerning a particular issue cannot be easily measured. Scaling is therefore used to assign a quantifiable value to qualitative responses to make it possible for the researcher to carry out data analysis (Cozby, 2009). The scales used in research studies are chosen and created according to the researcher’s preferences. However, it is important for the researcher to make the scale broad enough, for instance, to use a scale of 0-9 rather than a scale of 0-3 so as to accommodate all the possible responses from the respondents (Wimmer and Dominick, 2005).
References
Cozby, P. C. (2009). Methods in behavioral research (10th ed.). Boston: McGraw Hill Higher Education.
Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Thousand Oaks, CA: Sage Publications.
Trochim, W., & Donnelly, J. (2008). The research methods knowledge base (3rd ed.). Mason, OH: Cengage.
Wimmer, R. D., & Dominick, J. R. (2005). Mass media research: An introduction. New York: Wadsworth Publishing.