Variables: The Heart of Positivistic Research John L. Couper, Ph.D. 1. Variables are the tools used by positivistic studies to study change and/or comparison. a) Variable(s) that influence the change are independent variables: “systematically varied by the researcher or natural forces” that: exist before the dependent variable; are measurable; and whose characteristics lead to measurable change. There can be one or many independent variables. b) Variables that are being influenced are dependent variables: “which is observed and whose value is hypothesized to depend on the independent variable” that occur after the independent variable. There can be one or many dependent variables. c) Thus, the independent variable changes the dependent variable in ways that can be identified, isolated and measured. Most particular variables can be independent or dependent, depending on the hypothesized order and relationship between the two. As much as possible, these variables should be isolated from others that might distort the process, the “dependent measures”, and thus the results. d) In any social science study, effects are caused by complex factors with complex results. The goal is usually to find the “main effect”: the variable that explains most of the change at the center of the study. This is possible only if the variables and their relationships are clear. 2. One key goal of positivistic research is to * identify the variables as clearly and functionally as possible and * to isolate the variables so that (ideally) the effect measured is due to the role of that variable and nothing else. It is also important to make the study as simple, clear and “elegant” as possible: to reduce the variables so that However, since the world is complicated, other variables must be considered. a) extraneous variables are those that might seem related to the main variables, but which are irrelevant to the research and therefore must be excluded and/or controlled for. Most importantly, they must not be measured along with the variables under study. b) intervening variables are those that are secondary or unrelated to the main variables but that can influence them in ways that must be understood. * moderating variables influence the independent variable in ways that cannot be removed but that can act in a secondary way. Example: age, to the extent that it influences income * mediating variables influence the changes to the dependent variable after the influence of the independent variable. Example: a news story about a scandal after data is being collected on the effect of a media campaign. 3. The goal of controlling variables is to minimize the influence of any other influences except those being studied. Life is complicated; this is why experimental designs are so popular, even though they introduce other variables that might or might not influence the variables (such as laboratory conditions influencing how someone watches TV). There are many ways to improve research design, such as manipulation checks (pre-testing to make sure the survey collects the data needed, etc.), using a large sample size, removing intervening variables, using a control group to see what happens when the independent variable is not present, etc. 4. A study should strengthen theory and answer the following questions: a) is the topic interesting and extend the literature and the theory? b) are the research questions clear, specific and answerable? c) are the variables identifiable and distinct, and do they vary in ways that can be measured? d) if there are hypotheses, does the literature and/or theory predict interaction(s)? e) will the method collect valid data, and analyze it to credibly answer the research question?
Tip: an excellent way to work out variables is with medium-sized cards, one for each variable, arranged on a flat surface to develop and improve a “model� of the process being studied.
The two main goals of quantitative research are validity and reliability. a) validity is the assurance that what is being studied is the variable expected to be studied. Validity can include content validity (do the items measure what they are intended to measure?), predictive validity (do scores predict the expected change?), concurrent validity (do results correlate predictably with other variables at the same time?), construct validity (do items measure what is predicted by the theory?), and face validity (do the items seem to measure what the instrument used is designed to measure?). b) reliability is the consistency of a measurement across the time of the research, and allows testing of the variable in later research; mostly assumes the elimination of random errors of design or measurement. This can include item consistency (are the responses consistent?), test stability (do the same changes occur when the variable is measured additional times?), and consistency in administration and scoring (were errors caused by carelessless?).