{"pk":30212,"title":"Should we always log-transform looking time data in infancy research?","subtitle":null,"abstract":"Researchers often measure infants looking time (LT) as a dependent variable to measure how infants pay attention to certainstimuli. Using a large repository of data from their lab and the literature, Csibra and colleagues (2016) reported that thedistribution of LT is positively skewed and thus proposed that researchers should log-transform LT before running anyparametric analysis. In this study, we investigated whether log-transformation of LT will make the distribution normallydistributed by using data from a large-scale replication infancy study (ManyBabies Consortium (MB1), in press). Further,we simulated positively skewed LT data to examine whether log-transformation of LT would improve power. We foundthat log-transformation of the MB1 LT data did not make the LT data normally distributed. Also, we found that log-transformation of LT only slightly increased power. Implications and benefits of log-transformation of LT data will bediscussed.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Member Abstracts, appearing in proceedings only","is_remote":true,"remote_url":"https://escholarship.org/uc/item/6fg2g955","frozenauthors":[{"first_name":"Angeline","middle_name":"Sin Mei","last_name":"Tsui","name_suffix":"","institution":"Stanford University","department":""},{"first_name":"Michael","middle_name":"","last_name":"Frank","name_suffix":"","institution":"Stanford University","department":""},{"first_name":"Patricia","middle_name":"","last_name":"Brosseau-Liard","name_suffix":"","institution":"University of Ottawa","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2020-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/30212/galley/20066/download/"}]}