Methodological Urban Legends: The Misuse of Statistical Control Variables

By Paul E. Spector, Michael T. Brannick. 2011

1,127 citations recorded by the source corpus.

The automatic or blind inclusion of control variables in multiple regression and other analyses, intended to purify observed relationships among variables of interest, is widespread and can be considered an example of practice based on a methodological urban legend. Inclusion of such variables in most cases implicitly assumes that the control variables are somehow either contaminating the measurement of the variables of interest or affecting the underlying constructs, thus distorting observed relationships among them. There are, however, a number of alternative mechanisms that would produce the same statistical results, thus throwing into question whether inclusion of control variables has led to more or less accurate interpretation of results. The authors propose that researchers should be explicit rather than implicit regarding the role of control variables and match hypotheses precisely to both the choice of variables and the choice of analyses. The authors further propose that researchers avoid testing models in which demographic variables serve as proxies for variables that are of real theoretical interest in their data.

Subfields: Economics and Econometrics, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/58d9a442e6ec67ec5ca27d96814660ad58f8b9af

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

  1. Herman Aguinis
  2. Kevin D. Carlson
  3. Michael S. Cole
  4. Jeremy B. Bernerth
  5. K. Devine
  6. Jinpei Wu
  7. K. Hunter
  8. Allison S. Gabriel

In Sociology and Political Science

  1. Staale Einarsen
  2. H. Zacher
  3. M. B. Nielsen
  4. Laurenz L. Meier
  5. Lars Glasø
  6. Merideth Ferguson
  7. Ulla Kinnunen *
  8. Herman Aguinis

Citations in the corpus