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  "Package": "OLStrajr",
  "Title": "Ordinary Least Squares Trajectory Analysis",
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  "Authors@R": "c(\nperson(\"Mackson\", \"Ncube\", , \"macksonncube.stats@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"mightymetrika, LLC\", role = c(\"cph\", \"fnd\"))\n)",
  "Description": "The 'OLStrajr' package provides comprehensive functions\nfor ordinary least squares (OLS) trajectory analysis and\ncase-by-case OLS regression as outlined in Carrig, Wirth, and\nCurran (2004) <doi:10.1207/S15328007SEM1101_9> and Rogosa and\nSaner (1995) <doi:10.3102/10769986020002149>. It encompasses\ntwo primary functions, OLStraj() and cbc_lm(). The OLStraj()\nfunction simplifies the estimation of individual growth curves\nover time via OLS regression, with options for visualizing both\ngroup-level and individual-level growth trajectories and\nsupport for linear and quadratic models. The cbc_lm() function\nfacilitates case-by-case OLS estimates and provides unbiased\nmean population intercept and slope estimators by averaging OLS\nintercepts and slopes across cases. It further offers standard\nerror calculations across bootstrap replicates and computation\nof 95% confidence intervals based on empirical distributions\nfrom the resampling processes.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
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  "Date/Publication": "2023-06-22 15:34:55 UTC",
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