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  "Title": "Partial Eta-Squared for Crossed, Nested, and Mixed Linear Mixed\nModels",
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  "Authors@R": "c(\nperson(\"Brandon\", \"Cohen\", email = \"brandon.cohen-1@colorado.edu\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0009-0004-1802-3435\")),\nperson(\"Joshua\", \"Correll\", email = \"joshua.correll@colorado.edu\",\nrole = c(\"aut\", \"ths\"),\ncomment = c(ORCID = \"0000-0003-1142-459X\")))",
  "Description": "Computes partial eta-squared effect sizes for fixed\neffects in linear mixed models fitted with the 'lme4' package.\nSupports crossed, nested, and mixed (crossed-and-nested) random\neffects structures with any number of grouping factors. Mixed\ndesigns handle cases where grouping factors are simultaneously\ncrossed with some variables and nested within others (e.g.,\nphotos nested within models, but both crossed with\nparticipants). Random slope variances are translated to the\noutcome scale using a variance decomposition approach,\ncorrectly accounting for predictor scaling and interaction\nterms. Both general and operative effect sizes are provided.\nMethods are based on Correll, Mellinger, McClelland, and Judd\n(2020) <doi:10.1016/j.tics.2019.12.009>, Correll, Mellinger,\nand Pedersen (2022) <doi:10.3758/s13428-021-01687-2>, and\nRights and Sterba (2019) <doi:10.1037/met0000184>.",
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