week 11: Analyzing Data, Measurement: Scores, Indexes, Scales,

Indices, Scales and Typologies

Quantitative data analysis requires the construction of two types of measures of variables--indices and scales. These measures are frequently used and are important since social scientists often study variables that possess no clear and unambiguous indicators--for instance, age or gender. Researchers often centralize much of the work in regards to the attitudes and orientations of a group of people, which require several items to provide an indication of the variables. Secondly, researchers seek to establish ordinal categories from very low to very high (vice-versa), which single data items can not ensure, while an index or scale can.

Although they exhibit differences (which will later be discussed) the two have in common various factors. 
Both:

  • are ordinal measures of variables
  • can order the units of analysis in terms of specific variables
  • are composite measures of variables (measurements based on more than one one data item)

Indices are a sum of series of individual yes/no questions, that are then combined in a single numeric score. 
They are usually a measure of the quantity of some social phenomenon and are constructed at a ratio level of measurement. More sophisticated indices weigh individual items according to their importance in the concept being measured (i.e. in a multiple-choice test where different questions are worth different numbers of points). Some interval-level indices are not weight counted, but contain other indexes or scales within them (i.e. college admissions that score an applicant based on GPA, SAT scores, essays, and place a different point from each source).