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Arkistoitu opetusohjelma 2017–2018
Selaat vanhentunutta opetusohjelmaa. Voimassa olevan opetusohjelman löydät täältä.
DPIS1 Replication crisis and its solutions 1 ECTS
Periods
Period I Period II Period III Period IV
Language of instruction
English
Type or level of studies
Postgraduate studies
Course unit descriptions in the curriculum
Faculty of Natural Sciences

General description

Are most published research findings false (Ionnadis, 2005, Open Science Collaboration, 2015)? The course deals with the interpretations of and possible solutions to the lack of replicating results in empirical research (e.g. social psychology and cancer research). As a result of the lack of successful registered replications, a growing number journals such as Psychological Science are favouring practices such as direct replications and registered reports. The course gives a hands-on introduction to two methods which are thought to improve the reliability and replicability of empirical research: p-curve analysis and pre-registration.

The course:

  • Introduces participants to the ongoing conversation about the replicability of empirical research
  • Introduces participants to different interpretative frameworks of p-values and statistical significance (Null Hypothesis Significance Testing, Fisher, Neyman-Pearson, Bayes)
  • Provides participants with skills for pre-registration and p-curve analysis

Enrolment for University Studies

Enrolment time has expired

Teachers

Esa Palosaari, Teacher responsible
Esa.Palosaari[ät]uta.fi

Teaching

20-Nov-2017 – 15-Dec-2017
Tutorials
Lectures and exercises
Mon 20-Nov-2017 at 10.15-12.00, Linna ML50, Lack of replicating statistically significant results and their interpretations
Mon 20-Nov-2017 at 13.00-14.00, Linna ML50, Introduction to p-curve analysis and pre-registration
Mon 20-Nov-2017 at 14.15-16.00, Linna ML50, P-curve analysis and preregistration exercises

Evaluation

Pass/fail.

Evaluation criteria

Participation in course work and exercises.

Study materials

A list of readings / background material for the course:

Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251), aac4716.

Maxwell, S. E., Lau, M. Y., & Howard, G. S. (2015). Is psychology suffering from a replication crisis? What does “failure to replicate” really mean? American Psychologist, 70, 487-498.

Perezgonzales, J. D. (2015). Fisher, Neyman-Pearson or NHST? A tutorial for teaching data testing. Frontiers in Psychology, 6: 223.

Van Elk, M., Matzke, D., Gronau, Q. F., Guan, M., Vandekerckhove, J., & Wagenmakers, E. J. (2015). Meta-analyses are no substitute for registered replications: A skeptical perspective on religious priming. Frontiers in Psychology, 6.

Simonsohn, U., Nelson, L. D., & Simmons, J. P. (2014). P-curve: A key to the file-drawer. Journal of Experimental Psychology: General, 143(2), 534-547. http://dx.doi.org/10.1037/a0033242

Nosek, B. A., Spies, J. R., & Motyl, M. (2012). Scientific utopia II. Restructuring incentives and practices to promote truth over publishability. Perspectives on Psychological Science, 7, 615-631.

Further information

Masters Degree students of CBDA-programme: course can be included in the advanced studies of CBDA (Statistical Data Analytics). For details, contact your Personal Study Plan teacher.