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Sample size determination is a crucial aspect of research methodology that plays a significant role in ensuring the reliability and validity of study findings. In order to influence the accuracy of estimates, the power of statistical tests, and the general robustness of the research findings, it entails carefully choosing the number of ...
However, certain conditions must be met before the replication of the experiment is commenced: the original research question has been published in a peer-reviewed journal or widely cited, the researcher is independent of the original experiment, the researcher must first try to replicate the original findings using the original data, and the ...
In many studies and research designs, there may be a trade-off between internal validity and external validity: [16] [17] [18] Attempts to increase internal validity may also limit the generalizability of the findings, and vice versa. This situation has led many researchers call for "ecologically valid" experiments.
John Ioannidis argues that "claimed research findings may often be simply accurate measures of the prevailing bias." [46] He lists the following factors as those that make a paper with a positive result more likely to enter the literature and suppress negative-result papers: The studies conducted in a field have small sample sizes.
A 2021 study found that papers in leading general interest, psychology and economics journals with findings that could not be replicated tend to be cited more over time than reproducible research papers, likely because these results are surprising or interesting. The trend is not affected by publication of failed reproductions, after which only ...
Research findings cannot be easily conveyed to the participant. This is most commonly the case in addiction and criminal research. Additionally, findings may be difficult to understand. Member check exercises can make extensive demands on the participants' time.
"Why Most Published Research Findings Are False" is a 2005 essay written by John Ioannidis, a professor at the Stanford School of Medicine, and published in PLOS Medicine. [1] It is considered foundational to the field of metascience .
Under longitudinal research methods, the reduction in the research sample will bias the remaining smaller sample. [ citation needed ] Practice effect is also one of the problems: longitudinal studies tend to be influenced because subjects repeat the same procedure many times (potentially introducing autocorrelation ), and this may cause their ...