Researcher degrees of freedom

From Wikipedia, the free encyclopedia
Jump to navigation Jump to search

Researcher degrees of freedom is a concept referring to the inherent flexibility involved in the process of designing and conducting a scientific experiment, and in analyzing its results. The term reflects the fact that researchers can choose between multiple ways of collecting and analyzing data, and these decisions can be made either arbitrarily or because they, unlike other possible choices, produce a positive and statistically significant result.[1] Their widespread use represents an inherent methodological limitation in scientific research, and contributes to an inflated rate of false-positive findings.[1] They can also lead to overestimated effect sizes.[2]

Though the concept of researcher degrees of freedom has mainly been discussed in the context of psychology, it can affect any scientific discipline.[1] Like publication bias, the existence of researcher degrees of freedom has the potential to lead to an inflated degree of funnel plot asymmetry.[3] Furthermore, studies with smaller sample sizes are more susceptible to the biasing influence of researcher degrees of freedom.[4]


Steegen et al. (2016) showed how, starting from a single raw data set, applying different reasonable data processing decisions can give rise to a multitude of processed data sets (called the data multiverse), often leading to different statistical results.[5] Wicherts et al. (2016) provided a list of 34 degrees of freedom (DFs) researchers have when conducting psychological research. The DFs listed span every stage of the research process, from formulating a hypothesis to the reporting of results. They include conducting exploratory, hypothesis-free research, which the authors note "...pervades many of the researcher DFs that we describe below in the later phases of the study." Other DFs listed in this paper include the creation of multiple manipulated independent variables and the measurement of additional variables that may be selected for analysis later on.[2]


  1. ^ a b c Simmons, Joseph P.; Nelson, Leif D.; Simonsohn, Uri (November 2011). "False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant". Psychological Science. 22 (11): 1359–1366. doi:10.1177/0956797611417632. ISSN 0956-7976. PMID 22006061.
  2. ^ a b Wicherts, Jelte M.; Veldkamp, Coosje L. S.; Augusteijn, Hilde E. M.; Bakker, Marjan; van Aert, Robbie C. M.; van Assen, Marcel A. L. M. (2016-11-25). "Degrees of Freedom in Planning, Running, Analyzing, and Reporting Psychological Studies: A Checklist to Avoid p-Hacking". Frontiers in Psychology. 7: 1832. doi:10.3389/fpsyg.2016.01832. ISSN 1664-1078. PMC 5122713. PMID 27933012.
  3. ^ Carter, Evan C.; McCullough, Michael E. (2014-07-30). "Publication bias and the limited strength model of self-control: has the evidence for ego depletion been overestimated?". Frontiers in Psychology. 5: 823. doi:10.3389/fpsyg.2014.00823. ISSN 1664-1078. PMC 4115664. PMID 25126083.
  4. ^ Schweizer, Geoffrey; Furley, Philip (March 2016). "Reproducible research in sport and exercise psychology: The role of sample sizes". Psychology of Sport and Exercise. 23: 114–122. doi:10.1016/j.psychsport.2015.11.005.
  5. ^ Steegen, Sara; Tuerlinckx, Francis; Gelman, Andrew; Vanpaemel, Wolf (September 2016). "Increasing Transparency Through a Multiverse Analysis". Perspectives on Psychological Science. 11 (5): 702–712. doi:10.1177/1745691616658637. ISSN 1745-6916. PMID 27694465.