2012
DOI: 10.2139/ssrn.1996631
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Measuring the Prevalence of Questionable Research Practices with Incentives for Truth-Telling

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Cited by 236 publications
(394 citation statements)
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“…Simonsohn et al (2014) highlighted that researchers may file only the subsets of analyses that produce non-significant results, rather than placing entire studies in the file drawer, which is referred to as inflation bias or P-hacking. Recently, John et al (2012) showed that many researchers P-hack, but do not appreciate the extent to which this process is a form of scientific misconduct. Thus P-curve analysis can be used to assess whether the overall effect of the meta-analysis is due to P-hacking or true effect (Simonsohn et al, 2014).…”
Section: Publication Biasmentioning
confidence: 99%
“…Simonsohn et al (2014) highlighted that researchers may file only the subsets of analyses that produce non-significant results, rather than placing entire studies in the file drawer, which is referred to as inflation bias or P-hacking. Recently, John et al (2012) showed that many researchers P-hack, but do not appreciate the extent to which this process is a form of scientific misconduct. Thus P-curve analysis can be used to assess whether the overall effect of the meta-analysis is due to P-hacking or true effect (Simonsohn et al, 2014).…”
Section: Publication Biasmentioning
confidence: 99%
“…Unfortunately, many cases of scientific misconduct are never discovered (Fanelli 2009;John et al 2012). The number of retracted papers is increasing even when one accounts for the increasing number of papers being published (Cokol et al 2008).…”
mentioning
confidence: 99%
“…The debates about reproducibility have mostly focused on methodological issues, especially in relation to questionable research practices, such as selective reporting or gathering data until statistical significance is achieved [2]. Little attention has been paid to overgeneralization failures.…”
Section: Expected Outcomesmentioning
confidence: 99%