Dependent Variables Essay

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Dependent variables are presumed outcomes that can be influenced or predicted by other, independent variables. For example, providing scholarships to permit low income students to attend college (independent variable) might affect their occupations and income (dependent variables).

Dependent variables differ in the type of measurement (i.e., rules used to assign numerical values) they represent. Stevens (1946) identified four scales of measurement. In nominal scales, categories (e.g., teacher, lawyer) are arbitrarily assigned numerical values that convey no information other than category membership. Ordinal scales indicate the relative quality or amount of the variable of interest via rank ordering (e.g., drop out = 1; high school diploma = 2, associate’s degree = 3, bachelor’s degree = 4), but differences between ordinal scores are not meaningful (above, 2 — 1/4— 3). In interval scales (e.g., Fahrenheit temperatures), differences between numbers are invariant across the measurement scale (e.g., 42° — 37° = 84° — 79°). However, 84° Fahrenheit is not twice as hot as 42° Fahrenheit. Such statements can only be made for ratio scales, which have an absolute zero signifying absence of the thing being measured (e.g., Calvin temperatures, income in dollars). Thus, the level of measurement constrains the type of statistical analyses that are appropriate.

In interpreting the information provided by measurement of dependent variables, it is also essential to consider their reliability and validity. Reliability refers to the accuracy or precision of measurement. Validity, on the other hand, refers to the appropriateness and utility of the data for a given interpretation or use. Although data must be reliable in order to permit valid interpretations, misguided or erroneous interpretations of reliable data are possible. Thus, reliability is necessary but not sufficient for validity. Several approaches are used to gauge both reliability (e.g., internal consistency, test-retest) and validity (e.g., content, criterion-related).

Bibliography:

  • Stevens, S. (1946) On the theory of scales of measurement. Science 103: 677-80.

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