  The importance of research teams' diversity for the progress of science is
highlighted extensively. Despite the seemingly hegemonic role of hypothesis
testing in modern quantitative research, little attention has been devoted to
the diversity of quantitative methods, epitomized by the linear model framework
of analysis. Using bibliometric data from the Web of Science, we conduct a
large-scale and cross-disciplinary assessment of the prevalence of
linear-model-based research from 1990 to 2022. In absolute terms, linear models
are widely used across all fields of science. In relative terms, three patterns
suggest linear models are hegemonic among Social Sciences. First, there is a
high and growing prevalence of linear-model-based research. Second, global
patterns of linear-model-based research prevalence align with global
inequalities in knowledge production. Third, there was a citation premium to
linear-model-based research until 2012 for articles' number of citations and
for the entire period in terms of having at least one citation. Previous
research suggests that the confluence of these patterns may be detrimental to
the Social Sciences as it potentially marginalizes theories incompatible with
the linear models' framework, lowers the diversity of narratives about social
phenomena, and prevents innovative and path-breaking research, limiting the
breadth of research.
