Abstract
Empirical sciences in general and psychological science in particular are plagued by replicability problems and biased published effect sizes. Although dissemination bias-related phenomena such as publication bias, time-lag bias, or visibility bias are well-known and have been intensively studied, another variant of effect distorting mechanisms, so-called decline effects, have not. Conceptually, decline effects are rooted in low initial (exploratory) study power due to strategic researcher behavior and can be expected to yield overproportional effect declines. Although decline effects have been documented in individual meta-analytic investigations, systematic evidence for decline effects in the psychological literature remains to date unavailable. Therefore, we present in this meta-meta-analysis a systematic investigation of the decline effect in intelligence research. In all, data from 22 meta-analyses comprising 36 meta-analytical and 1,391 primary effect sizes (N = 697,000+) that have been published in the journal Intelligence were included in our analyses. Two different analytic approaches showed consistent evidence for a higher prevalence of cross-temporal effect declines compared to effect increases, yielding a ratio of about 2:1. Moreover, effect declines were considerably stronger when referenced to the initial primary study within a meta-analysis, yielding about twice the magnitude of effect increases. Effect misestimations were more substantial when initial studies had smaller sample sizes and reported larger effects, thus indicating suboptimal initial study power as the main driver of effect misestimations in initial studies. Post hoc study power comparisons of initial versus subsequent studies were consistent with this interpretation, showing substantially lower initial study power of declining, than of increasing effects. Our findings add another facet to the ever accumulating evidence about non-trivial effect misestimations in the scientific literature. We therefore stress the necessity for more rigorous protocols when it comes to designing and conducting primary research as well as reporting findings in exploratory and replication studies. Increasing transparency in scientific processes such as data sharing, (exploratory) study preregistration, but also self- (or independent) replication preceding the publication of exploratory findings may be suitable approaches to strengthen the credibility of empirical research in general and psychological science in particular.
Highlights
The credibility of results from empirical research in general and psychological science in particular depends on the reproducibility of published results
That initial study effects misestimated observed summary effects by a small-tomoderate effect size regardless of their direction
Detailed results of influence diagnostics are provided in the Supplementary Data Sheet S1. In this meta-meta-analysis, we show that effect declines over time systematically outnumber effect increases at a ratio of about two to one
Summary
The credibility of results from empirical research in general and psychological science in particular depends on the reproducibility of published results. Self-admittance rates of fraudulent practices are low (but not nil; see, Fiedler and Schwarz, 2016), other research practices and researcher behaviors that cause effect misestimation (i.e., systematic over- vs underestimation) may play a more important role: Strategic research and submission behaviors, selective reporting, and p-hacking (see e.g., Bakker et al, 2012; Simonsohn et al, 2014) are only some of the mechanisms that may lead to a disproportionate number of biased effects in the scientific literature Such behaviors appear to be quite common, as self-admission rates and prevalence estimates suggest that the majority of researchers in psychology have engaged in at least one of these questionable research practices (e.g., John et al, 2012). A recent review of 64 studies that addressed this topic showed that evidence for such practices almost invariably emerged, regardless of the investigated subdiscipline (Banks et al, 2016)
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