crosslag: Perform Linear or Nonlinear Cross Lag Analysis

Linear or nonlinear cross-lagged panel model can be built from input data. Users can choose the appropriate method from three methods for constructing nonlinear cross lagged models. These three methods include polynomial regression, generalized additive model and generalized linear mixed model.In addition, a function for determining linear relationships is provided. Relevant knowledge of cross lagged models can be learned through the paper by Fredrik Falkenström (2024) <doi:10.1016/j.cpr.2024.102435> and the paper by A Gasparrini (2010) <doi:10.1002/sim.3940>.

Version:	0.1.0
Depends:	R (≥ 4.3.0)
Imports:	gamm4 (≥ 0.2.6), ggplot2 (≥ 3.5.0), lavaan (≥ 0.6.17), mgcv (≥ 1.9.1), rms (≥ 6.8.0), ggpubr (≥ 0.6.0), stats (≥ 4.3.2), utils (≥ 3.1.0)
Published:	2024-05-17
DOI:	10.32614/CRAN.package.crosslag
Author:	Yaxin Li [aut, cre]
Maintainer:	Yaxin Li <LYX010308 at 163.com>
License:	MIT + file LICENSE
NeedsCompilation:	no
In views:	TimeSeries
CRAN checks:	crosslag results

Documentation:

Reference manual:

crosslag.pdf

Downloads:

Package source:	crosslag_0.1.0.tar.gz
Windows binaries:	r-devel: crosslag_0.1.0.zip, r-release: crosslag_0.1.0.zip, r-oldrel: crosslag_0.1.0.zip
macOS binaries:	r-release (arm64): crosslag_0.1.0.tgz, r-oldrel (arm64): crosslag_0.1.0.tgz, r-release (x86_64): crosslag_0.1.0.tgz, r-oldrel (x86_64): crosslag_0.1.0.tgz

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