Date created: | Last Updated:

Category: Project

Description: Editorial of the Journal of Media Psychology special issue on "Technology & Human Behavior", and meta-analysis of the empirical research published in JMP since 2008. DATA AVAILABILITY We were not able to identify a single publication reporting a link to research data in a public repository or the journal’s supplementary materials. STATISTICAL REPORTING ERRORS We extracted a total of 1036 NHSTs reported in 98 articles. 129 tests were flagged as inconsistent (i.e., reported test statistics and degrees of freedom do not match reported p-values), of which 23 were grossly inconsistent (the reported p-value is <.05 while the recomputed p-value is >.05, or vice-versa). 41 publications reported at least one inconsistent NHST, and 16 publications reported at least one grossly inconsistent NHST. Thus, a substantial proportion of publications in JMP seem to contain inaccurately reported statistical analyses, of which some might affect the conclusions drawn from them. STATISTICAL POWER As in other fields, surveys tend to have healthy sample sizes apt to reliably detect medium to large relationships between variables. The median sample size for survey studies is 327, allowing researchers to detect small bivariate correlations of r=.1 at 44% power (rs=.3/.5 both > 99%). For (quasi-)experiments, the outlook is a bit different, with a median sample size of 107. Across all types of designs, the median condition size is 30.67. Thus, the average power of experiments published in JMP to detect small differences between conditions (d=.20) is 12% (d=.50 at 49%, d=.80 at 87%).