Path.Analysis
Path Coefficient Analysis
Facilitates the performance of several analyses, including simple and sequential path coefficient analysis, correlation estimate, drawing correlogram, Heatmap, and path diagram. When working with raw data, that includes one or more dependent variables along with one or more independent variables are available, the path coefficient analysis can be conducted. It allows for testing direct effects, which can be a vital indicator in path coefficient analysis. The process of preparing the dataset rule is explained in detail in the vignette file "Path.Analysis_manual.Rmd". You can find this in the folders labelled "data" and "~/inst/extdata". Also see: 1)the 'lavaan', 2)a sample of sequential path analysis in 'metan' suggested by Olivoto and Lúcio (2020) <doi:10.1111/2041-210X.13384>, 3)the simple 'PATHSAS' macro written in 'SAS' by Cramer et al. (1999) <doi:10.1093/jhered/90.1.260>, and 4)the semPlot() function of 'OpenMx' as initial tools for conducting path coefficient analyses and SEM (Structural Equation Modeling). To gain a comprehensive understanding of path coefficient analysis, both in theory and practice, see a 'Minitab' macro developed by Arminian, A. in the paper by Arminian et al. (2008) <doi:10.1080/15427520802043182>.
README
## Summary
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
R package **Path.Analysis** provides a comprehensive textual and illustrative analysis on raw data or a correlation matrix
to extract correlation coefficients, path direct and indirect effect along with testing direct effects.
Later, it draws 3 kinds of correlation plot, diagram and a Heatmap.
'Path.Analysis' is very easy to use and provides a good plotting options in
visualization method, graphic layout, color, legend, text labels, etc.
It also provides p-values of direct effects to help users determine the
statistical significance of the correlations and direct effects.
For examples, see its
#[online vignette](https://github.com/abeyran/Path.Analysis).
This package is licensed under the MIT license, and available on CRAN:
<https://cran.r-project.org/package=Path.Analysis>.
## Basic examples
```r
library(Path.Analysis)
data(dtsimp)
Path.Analysis(dtsimp, 1, rplot = FALSE, rdend = FALSE)
```
```r
library(Path.Analysis)
data(dtraw)
Path.Analysis(dtraw, 1, rplot = TRUE, rdend = FALSE)
```
## Download and Install
To download the release version of the package on CRAN, type the following at the R command line:
```r
install.packages('Path.Analysis')
```
To download the development version of the package, type the following at the R command line:
```r
devtools::install_github('abeyran/Path.Analysis', build_vignettes = TRUE)
```
## How to cite
To cite `corrplot` properly, call the R built-in command
`citation('Path.Analysis')` as follows:
```r
citation('Rapth')
```
## Reporting bugs and other issues
If you encounter a clear bug, please file a minimal reproducible example on
[github](https://github.com/abeyran/Path.Analysis/issues).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1 |
rolling linux/jammy R-4.5 | Path.Analysis_0.1.tar.gz |
1.0 MiB |
0.1 |
rolling linux/noble R-4.5 | Path.Analysis_0.1.tar.gz |
1.0 MiB |
0.1 |
rolling source/ R- | Path.Analysis_0.1.tar.gz |
1.0 MiB |
0.1 |
latest linux/jammy R-4.5 | Path.Analysis_0.1.tar.gz |
1.0 MiB |
0.1 |
latest linux/noble R-4.5 | Path.Analysis_0.1.tar.gz |
1.0 MiB |
0.1 |
latest source/ R- | Path.Analysis_0.1.tar.gz |
1.0 MiB |
0.1 |
2026-04-26 source/ R- | Path.Analysis_0.1.tar.gz |
1.0 MiB |
0.1 |
2026-04-23 source/ R- | Path.Analysis_0.1.tar.gz |
1.0 MiB |
0.1 |
2025-04-20 source/ R- | Path.Analysis_0.1.tar.gz |
1.0 MiB |