Download MP3 45 min. Today we welcome Dr. Daryl Bem to Skeptiko.
Steven Novella on August 29, Shares I love reading quotes by the likes of Karl Popper in the scientific literature. All of the studies followed a similar format, reversing the usually direction of standard psychology experiments to determine if future events can affect past performance.
They were then asked to recall as many of the words as possible. Following that they were given two practice sessions with half of the word chosen by the computer at random.
Needles to say, these results were met with widespread skepticism. There are a number of ways to assess an experiment to determine if the results are reliable.
You can examine the methods and the data themselves to see if there are any mistakes. You can also replicate the experiment to see if you get the same results.
This decision and editorial policy was widely criticized, as it reflects an undervaluing of replications. Galak, LeBoeuf, Nelson, and Simmons should be commended, not only on their rigorous replication but their excellent article, which hits all the key points of this entire episode.
The researchers replicated experiments 8 and 9 of Bem they chose these protocols because they were the most objective. Six of the seven studies, when analyzed independently, were negative, while the last was slightly statistically significant.
However, when the data are taken together, they are dead negative. The authors concluded that their experiments found no evidence for psi. This involves considering a claim for plausibility and prior probability.
Bem and others are fairly dismissive of plausibility arguments and feel that scientists should be open to whatever the evidence states. If we dismiss results because we have already decided the phenomenon is not real, then how will we ever discover new phenomena? On the other hand, it seems like folly to ignore the results of all prior research and act as if we have no prior knowledge.
There is a workable compromise — be open to new phenomena, but put any research results into the context of existing knowledge. What this means is that we make the bar for rigorous evidence proportional to the implausibility of the phenomenon being studied.
Extraordinary claims require extraordinary evidence. One specific manifestation of this issue is the nature of the statistical analysis of research outcomes. Some researchers propose that we use a Bayesian analysis of data, which in essence puts the new research data into the context of prior research.
A Bayesian approach essentially asks — how much does this new data affect the prior probability that an effect is real? They further claim that the currently in vogue P-value analysis tends to overcall positive results. In reply Bem claims that Wagenmakers used a ridiculously low prior probability in his analysis.
Galak et al in the new study also perform a Bayesian analysis of their own data and conclude that this analysis strongly favors the null hypothesis. They mention the Bayesian issue, but also that an analysis of the data shows an inverse relationship between effect size and subject number.
In other words, the fewer the number of subjects the greater the effect size. This could imply a process called optional stopping. This is potentially very problematic. Related to this is the admission by Bem, according to the article, that he peeked at the data as it was coming in.
The reason peeking is frowned upon is precisely because it can result in things like optional stopping, which is stopping the collection of data in an experiment because the results so far are looking positive. This is a subtle way of cherry picking positive data. It is preferred that a predetermined stopping point is chosen to prevent this sort of subtle manipulation of data.
Another issue raised was the use of multiple analysis. Researchers can collect lots of data, by looking at many variables, and then making many comparisons among those variables. Sometimes they only publish the positive correlations, and may or may not disclose that they even looked at other comparisons.
Sometimes they publish all the data, but the statistical analysis treats each comparison independently. You can then declare a real effect.SAMPLE EXCERPT:  Bem was a critic of cognitive dissonance theory.
He designed a replication of the original Festinger & Carlsmith () study. In Bem's () version participants listened to a tape recorded description of the cognitive dissonance experiment of a man enthusiastically describing the boring task. Dr. Daryl Bem: It’s unusual because it’s a controversial area of research.
So I’m not familiar with that kind of operation in virtually any other areas of psychology. So I’m not familiar with that kind of operation in virtually any other areas of psychology.
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How to Write a Good Scientific Paper: Review Articles Chris Mack Chris Mack, “How to Write a Good Scientific Paper: Review Articles,” J. Micro/Nanolith. † The quality of the paper (method and execution of the research, as well as the writing) must be sufficiently high Daryl J.
Bem, “Writing a Review Article for Psychological. Dr. Daryl Bem: It’s unusual because it’s a controversial area of research. So I’m not familiar with that kind of operation in virtually any other areas of psychology.
So I’m not familiar with that kind of operation in virtually any other areas of psychology. Daryl J. Bem Cornell University Planning it 2 Which Article Should You Write 2 Research Participants 21 Sex and Gender 21 Writing the Empirical Journal Article 4 ers to read the report from beginning to end, as they would any coherent narra-tive, but also to scan it for a quick overview of the study or to locate specific in-.