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Description: The transparency and openness movement, along with research on researcher analysis practices (i.e., Many Analysts studies) have made it clear that one has many options for processing and analyzing data. With the increase in computational ability, researchers can now test multiple versions of an analysis pipeline using multiverse analysis. Multiverse analysis allows for the investigation of the impact of specific pipeline choices on the outcome of interest, as well as the potential range of possible effects given those analysis choices. This workshop will explore multiverse analysis for research in language sciences, which often deals with the added complexity of multi-level designs using varied stimuli to assess their phenomenon of interest. The workshop will provide general examples using priming data and specific R coding techniques that can be leveraged to complete a multiverse analysis.