Simmons et al. (2011) false positive psychology Flashcards
false positives, and why they are a problem
the incorrect rejection of a null hypothesis.
- once they appear in the literature, false positives are particularly persistent. researchers have little incentive to do replications because journals do not like to publish null-results. failed replications are not conclusive.
- waste resources by leading researchers astray, leads to ineffective policies, undermines credibility of field of research
researcher’s degrees of freedom
decisions a researcher can make. For example: Should more data be collected? Should some observations be excluded? Which conditions should be combined and which ones compared? Which control variables should be considered? Should specific measures be combined or transformed or both?
Problem with researcher degree of freedom
it is accepted to make these decisions during analysis, after obtaining the results, which increase the chance of type I errors.
Reasons for exploratory behaviors
- ambiguity on how to best make methodological decisions. Confirmation bias and hindsight bias.
- the researcher’s desire to find statistical results.
-> Confirmation bias and hindsight bias.
researcher degrees of freedom examined in simulation study (4)
flexibility in (a) choosing among dependent variables, (b) choosing sample size, (c) using covariates, and (d) reporting subsets of experimental conditions
Results of simulation study
every single researcher degree of freedom could be used to increase the rate of significant results. Combining them led to even more significant results, see table in article or lecture slides.
effect of optional stopping
in general, we have the intuition that an effect that is insignificant at a low sample size will not turn significant when adding observations. It turns out this is not true. Optional stopping can be effectively used to generate false positives.
the six requirements for authors of good research
Requirements for authors
- Authors must decide the rule for terminating data collection before data collection begins and report this rule in the article.
- Authors must collect at least 20 observations per cell or else provide a compelling cost-of-data-collection justification.
- Authors must list all variables collected in a study.
- Authors must report all experimental conditions, including failed manipulations.
- If observations are eliminated, authors must also report what the statistical results are if those observations are included.
- If an analysis includes a covariate, authors must report the statistical results of the analysis without the covariate.
Why should authors determine a rule on when to terminate data collection
To prevent type I errors through convenient stopping once a significant result is reached. The justification of the rule is secondary, most important is that this rule actually exists.
Why should there be at least 20 observations per cell?
To have a minimum required amount of power. It is a general assumption.
Why must authors list all variables and all experimental conditions?
To prevent them from selecting a convenient subset. The reader can get an idea of the researcher’s degrees of freedom.
Why must the author report the results without excluding outliers? Why does he have to do the same with covariates?
to pressure him to carefully exclude cases and to make things transparent for the reader. Same reasoning goes for the covariates.
What are the guidelines for reviewers?
- Reviewers should ensure that authors follow the requirements.
- Reviewers should be more tolerant of imperfections in results.
- Reviewers should require authors to demonstrate that their results do not hinge on arbitrary analytic decisions.
- If justifications of data collection or analysis are not compelling, reviewers should require the authors to conduct an exact replication.
Problems not addressed by the requirements of the article
file-drawer problem: not reporting insignificant experiments.
Enforcement of the disclosure requirements: researchers are not incentivized to disclose everything. Article argues that the reviewers are responsible for enforcement.
Why correcting alpha levels is not a solution to the researchers degree of freedom problem
We cannot know how many degrees of freedom exist in a given situation. Creates ambiguities.