 Feb 2021

psyarxiv.com psyarxiv.com

Lakens, D. (2021). Sample Size Justification. PsyArXiv. https://doi.org/10.31234/osf.io/9d3yf

 Oct 2020

stats.idre.ucla.edu stats.idre.ucla.edu

Power Analyses
Power Analyses with SPSS, R, Stata, SAS

 Jul 2020


Garmendia, A., & Alfonso, S. L. (2020). Popular Reactions To External Threats in Federations. https://doi.org/10.31235/osf.io/qyjtm


psyarxiv.com psyarxiv.com

OlssonCollentine, A., van Assen, M. A. L. M., & Wicherts, J. M. (2020). Postprint—Heterogeneity in direct replications in psychology and its association with effect size [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/m23v4



Du, H., Jiang, G., & Ke, Z. (2020). A Bootstrap Based BetweenStudy Heterogeneity Test in MetaAnalysis [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/de4g9

 Mar 2020

stats.idre.ucla.edu stats.idre.ucla.edu

Factors that affect power
Factors that affect power.

Cohen’s recommendations: Jacob Cohen has many wellknown publications regarding issues of power and power analyses, including some recommendations about effect sizes that you can use when doing your power analysis. Many researchers (including Cohen) consider the use of such recommendations as a last resort, when a thorough literature review has failed to reveal any useful numbers and a pilot study is either not possible or not feasible. From Cohen (1988, pages 2427):
Recommendations from Cohen about choosing the effect size when doing a power analysis.

Obtaining the necessary numbers to do a power analysis
Obtaining the necessary numbers to do a power analysis

Power is the probability of detecting an effect, given that the effect is really there. In other words, it is the probability of rejecting the null hypothesis when it is in fact false. For example, let’s say that we have a simple study with drug A and a placebo group, and that the drug truly is effective; the power is the probability of finding a difference between the two groups. So, imagine that we had a power of .8 and that this simple study was conducted many times. Having power of .8 means that 80% of the time, we would get a statistically significant difference between the drug A and placebo groups. This also means that 20% of the times that we run this experiment, we will not obtain a statistically significant effect between the two groups, even though there really is an effect in reality.
Power analysis definition
