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Most multilevel methodologies can only model macro-micro multilevel situations in an unbiased way, wherein group-level predictors (e.g., city temperature) are used to predict an individual-level outcome variable (e.g., citizen personality). In contrast, this R package enables researchers to model micro-macro situations, wherein individual-level (micro) predictors (and other group-level predictors) are used to predict a group-level (macro) outcome variable in an unbiased way.
| Version: | 0.4.0 |
| Depends: | R (≥ 3.1.0) |
| Published: | 2017-07-01 |
| DOI: | 10.32614/CRAN.package.MicroMacroMultilevel |
| Author: | Jackson G Lu [aut], Elizabeth Page-Gould [aut], Nancy R Xu [aut, cre] |
| Maintainer: | Nancy R Xu <nancyranxu at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | MicroMacroMultilevel results |
| Reference manual: | MicroMacroMultilevel.pdf |
| Package source: | MicroMacroMultilevel_0.4.0.tar.gz |
| Windows binaries: | r-devel: MicroMacroMultilevel_0.4.0.zip, r-release: MicroMacroMultilevel_0.4.0.zip, r-oldrel: MicroMacroMultilevel_0.4.0.zip |
| macOS binaries: | r-release (arm64): MicroMacroMultilevel_0.4.0.tgz, r-oldrel (arm64): MicroMacroMultilevel_0.4.0.tgz, r-release (x86_64): MicroMacroMultilevel_0.4.0.tgz, r-oldrel (x86_64): MicroMacroMultilevel_0.4.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.