If a research team conducts an experiment using a point value of .05 and gets statistically significant results, there is still a 5% possibility that their results are due to chance. This, combined with ________, are two main contributing factors to the reproducibility crisis.
Answers
Answer:As addressed elsewhere in this course, within psychology we use the scientific method as our tool to advance our knowledge within the field. Using this method we take our current understanding of the psychological world, and from that we derive testable hypotheses about our theoretical models. We test those hypotheses by gathering data, we openly share our methodology and our data via peer-reviewed publication, and based on these data we draw conclusions about the implications for our theoretical models of psychology.
Within this model, our current understanding of psychology is built on all the published research that exists within the field. This includes historical research, and it includes the newer research that has since superseded the historical data. Those who conduct research in the field today derive their hypotheses from the aggregated body of research that has taken place in the past.
The Role of Replication
The openness of psychological research – sharing our methodology and data via publication – is a key to the effectiveness of the scientific method. This allows other psychologists to know exactly how data were gathered, and it allows them to potentially use the same methods to test new hypotheses.
In an ideal world, this openness also allows other researchers to check whether a study was valid by replication – essentially, using the same methods to see if they yield the same results. The ability to replicate allows us to hold researchers accountable for their work.
Statistics and p-values
Replication is particularly important in a field such as psychology, which relies on statistics for its data. Human beings are a very diverse group, and so any study of human psychology will yield a diverse set of results. Statistics are used to identify the hidden patterns within the overall noisy and diverse data of human psychology.
The challenge within statistics is that sometimes randomness doesn’t look random. For instance, if you toss a coin 100 times, then most of the time you’ll get about 50 heads and 50 tails. But if a hundred people each toss a coin a hundred times, then some of those people will get 60 heads and 40 tails, or even 70 heads and 30 tails. Some people will get stretches where heads come up 10 times in a row. The question, then, is whether these kinds of patterns happened for a reason, or happened just out of randomness. That’s where statistics come in.
Many statistics are used in the field of psychology, and many yield results in the form of what is called a p-value. As noted previously in our course, a p-value is a statement of probability, the probability that a given result was just a result of randomness.
Such statistics are used in many fields – psychology, economics, medicine – and within each field there are generally accepted standards for p-values. Within psychology, the most common standard for p-values is “p < .05”. What this means is that there is less than a 5% probability that the results happened just by random chance, and therefore a 95% probability that a results reflects a meaningful pattern in human psychology. We call this statistical significance, and, statistically speaking, this is a pretty high standard. You need a pretty defined pattern within a research sample to reach that threshold.
However, this standard contains two problems. The first is that, if your sample is large enough, you can get a statistically significant p-value for a pretty small effect. So, while we may be able to say that a result is statistically significant, it might not actually be all that interesting in the context of how we understand human psychology.
The greater problem, however, comes when we multiple p-values over many studies. It’s one thing to say that we have only a 5% chance that a result came from randomness within one study. However, when we publish thousands of studies a year, all with the standard of p < .05, we must conclude that some nontrivial number of those studies are built around results that were, in fact, random. A 5% probability of randomness multiplied across thousands of studies makes this inevitable.
Answer:
The correct answer is publication bias.
Explanation:
- The results of numerous scientific research have been found to be challenging or impossible to repeat, leading to the replication crisis, also known as the reproducibility crisis.
- Such failures cast doubt on the validity of hypotheses based on empirical findings and may even bring important areas of scientific knowledge into question because the replication of empirical results is a crucial component of the scientific process.
- Publication bias in academic research happens when the results of an experiment or study influence the decision to publish or distribute it in some other way.
- The balance of findings in favour of positive results is disturbed when only studies with a significant finding are published.
Chance and publication bias contribute to reproducibilty crisis.
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