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Both models account for within-subject (cell\nline) correlation while holding different distributional\nassumptions about the outcome. Alternatively, the counterparts\nof fixed effects model are also available, which produces\nsimilar estimates of statistical power.", "License": "GPL (>= 2)", "Encoding": "UTF-8", "RoxygenNote": "7.3.2", "Language": "en-US", "LazyData": "true", "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev zlib1g-dev", "Repository": "https://shanpengli.r-universe.dev", "Date/Publication": "2025-12-15 00:46:07 UTC", "RemoteUrl": "https://github.com/shanpengli/pdxpower", "RemoteRef": "HEAD", "RemoteSha": "e1839fa403dd583232d5c9bbdfaed13d4430006b", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-15 10:20:02 UTC", "User": "root" }, "Author": "Shanpeng Li [aut, cre],\nGang Li [ctb]", "MD5sum": "62e96efb0df756f151413b18ea435e1e", "_user": "shanpengli", "_type": "src", "_file": "PDXpower_1.0.5.tar.gz", "_fileid": "25f90fb996a89cf0835a1234292026940f817af3e733185ffa525b87577f5c0e", "_filesize": 301533, "_sha256": "25f90fb996a89cf0835a1234292026940f817af3e733185ffa525b87577f5c0e", "_created": 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