{ "_id": "6ab22f8d3d719c1f84089fef", "Package": "silp", "Title": "Conditional Process Analysis (CPA) via SEM Approach", "Version": "1.0.3", "Authors@R": "c(person(\"Yi-Hsuan\", \"Tseng\", , \"r12227115@g.ntu.edu.tw\", role = c(\"aut\", \"cre\")),\nperson(\"Po-Hsien\", \"Huang\", , \"psyphh@nccu.edu.tw\", role = c(\"aut\")))", "Description": "Utilizes the Reliability-Adjusted Product Indicator (RAPI)\nmethod to estimate effects among latent variables, thus\nallowing for more precise definition and analysis of mediation\nand moderation models. Our simulation studies reveal that while\n'silp' may exhibit instability with smaller sample sizes and\nlower reliability scores (e.g., N = 100, 'omega' = 0.7),\nimplementing nearest positive definite matrix correction and\nbootstrap confidence interval estimation can significantly\nameliorate this volatility. When these adjustments are applied,\n'silp' achieves estimations akin in quality to those derived\nfrom LMS. In conclusion, the 'silp' package is a valuable tool\nfor researchers seeking to explore complex relational\nstructures between variables without resorting to commercial\nsoftware. Cheung et al.(2021)\nHsiao et al.(2018).", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.2", "NeedsCompilation": "no", "Packaged": { "Date": "2026-09-22 07:31:19 UTC", "User": "root" }, "Maintainer": "Yi-Hsuan Tseng ", "URL": "https://github.com/TomBJJJ/silp", "BugReports": "https://github.com/TomBJJJ/silp/issues", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://tombjjj.r-universe.dev", "Date/Publication": "2025-04-06 08:40:35 UTC", "RemoteUrl": "https://github.com/tombjjj/silp", "RemoteRef": "HEAD", "RemoteSha": "02d76a0446170d362c906ed4d5ae082106771074", "Author": "Yi-Hsuan Tseng [aut, cre],\nPo-Hsien Huang [aut]", "_user": "tombjjj", "_type": "src", "_file": "silp_1.0.3.tar.gz", "_fileid": "https://r2.ropensci.org/cc44d215ab62dd7084bad5abb209ae69f9cfb235b59b42318f9f2e2229350088", "_filesize": 117494, "_sha256": "cc44d215ab62dd7084bad5abb209ae69f9cfb235b59b42318f9f2e2229350088", "_expires": 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