Package: Path.Analysis 0.1

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>.

Authors:Ali Arminian [aut, cre, cph]

Path.Analysis_0.1.tar.gz
Path.Analysis_0.1.zip(r-4.7)Path.Analysis_0.1.zip(r-4.6)Path.Analysis_0.1.zip(r-4.5)
Path.Analysis_0.1.tgz(r-4.6-any)Path.Analysis_0.1.tgz(r-4.5-any)
Path.Analysis_0.1.tar.gz(r-4.7-any)Path.Analysis_0.1.tar.gz(r-4.6-any)
Path.Analysis_0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
Path.Analysis/json (API)
NEWS

# Install 'Path.Analysis' in R:
install.packages('Path.Analysis', repos = c('https://abeyrann.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/abeyran/path.analysis/issues

Datasets:
  • dtraw - Dataset 2: a number of 9 traits measured on 35 Camelina DH lines.
  • dtraw2 - Dataset 3: a number of 9 traits measured on 35 Camelina DH lines.
  • dtseq - Dataset 4: a dataframe consisting of 7 variables measured on 8 observations.
  • dtseqr - Dataset5
  • dtsimp - Dataset 1: a dependent (y) and 3 independent(x1 to x3) variables.
  • heart - Dataset 6: Heart Disease data set

On CRAN:

Conda:

2.70 score 2 scripts 239 downloads 8 exports 136 dependencies

Last updated from:b0758c129c. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE226
source / vignettesOK247
linux-release-x86_64NOTE230
macos-release-arm64NOTE159
macos-oldrel-arm64NOTE224
windows-develNOTE128
windows-releaseNOTE130
windows-oldrelNOTE178
wasm-releaseOK172

Exports:cor_plotcorrdataprepdescheat_mapmatdiagnetwork.plotreg

Dependencies:backportsbase64encBiocGenericsbitbit64bitopsbootbslibcacachemcaToolscheckmatecirclizeclicliprclueclustercodetoolscolorspaceComplexHeatmapcorrplotcorrrcpp11crayondata.tableDiagrammeRdigestdoParalleldplyrevaluatefarverfastmapfontawesomeforcatsforeachforeignFormulafsgclusgenericsGetoptLongGGallyggforceggplot2ggrepelggstatsGlobalOptionsgluegplotsgridExtragtablegtoolshighrHmischmshtmlTablehtmltoolshtmlwidgetsigraphIRangesisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelifecyclelme4lmerTestmagrittrMASSmathjaxrMatrixmatrixStatsmemoisemetanmgcvmimeminqanlmenloptrnnetnumDerivpastecspatchworkpermutepillarpkgconfigpngpolyclipprettyunitsprogresspurrrqapR6rappdirsrbibutilsRColorBrewerRcppRcppEigenRdpackreadrreformulasregistryrjsonrlangrmarkdownrpartrstudioapiS4VectorsS7sassscalesseriationshapestringistringrsystemfontstibbletidyrtidyselecttinytexTSPtweenrtzdbutf8vctrsveganviridisLitevisNetworkvroomwithrxfunyaml

Path Coefficient Analysis

Rendered fromPath.Analysis_manual.Rmdusingknitr::rmarkdownon May 08 2026.

Last update: 2024-09-25
Started: 2024-09-25