Package: multilevel 2.7

Paul Bliese

multilevel: Multilevel Functions

Tools used by organizational researchers for the analysis of multilevel data. Includes four broad sets of tools. First, functions for estimating within-group agreement and reliability indices. Second, functions for manipulating multilevel and longitudinal (panel) data. Third, simulations for estimating power and generating multilevel data. Fourth, miscellaneous functions for estimating reliability and performing simple calculations and data transformations.

Authors:Paul Bliese [aut, cre], Gilad Chen [ctb], Patrick Downes [ctb], Donald Schepker [ctb], Jonas Lang [ctb]

multilevel_2.7.tar.gz
multilevel_2.7.tar.gz(r-4.5-noble)multilevel_2.7.tar.gz(r-4.4-noble)
multilevel_2.7.tgz(r-4.4-emscripten)multilevel_2.7.tgz(r-4.3-emscripten)
multilevel.pdf |multilevel.html✨
multilevel/json (API)

# Install 'multilevel' in R:
install.packages('multilevel', repos = 'https://cloud.r-project.org')
Datasets:
  • bh1996 - Data from Bliese and Halverson
  • bhr2000 - Data from Bliese, Halverson and Rothberg
  • chen2005 - Data from Chen
  • cohesion - Small nested cohesion data frame
  • klein2000 - Data from Klein, Bliese, Kozlowski et al.,
  • lq2002 - Data used in special issue of Leadership Quarterly, Vol. 13, 2002
  • paneldat - Firm-Level Panel Data from Donald J. (DJ) Schepker
  • sherifdat - Sherif (1935) group data from 3 person teams
  • tankdat - Tank data from Bliese and Lang
  • univbct - Data from Bliese and Ployhart

On CRAN:

Conda:r-multilevel-2.7(2025-03-25)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.79 score 4 packages 5.2k downloads 28 mentions 41 exports 3 dependencies

Last updated 3 years agofrom:d0c02975a2. Checks:2 OK, 1 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 04 2025
R-4.5-linuxNOTEMar 04 2025
R-4.4-linuxOKMar 04 2025

Exports:ad.mad.m.simawgboot.icccordifcordif.depcronbachdgm.codegmeanrelgraph.ran.meanICC1ICC2item.totalmake.univmix.datamult.iccmult.make.univquantile.agree.simquantile.disagree.simquantile.rgr.wabaran.grouprgr.agreergr.olsrgr.wabarmv.blanksrtozrwgrwg.jrwg.j.lindellrwg.j.simrwg.simsam.corsim.iccsim.mlcorsimbiassobelsummary.agree.simsummary.disagree.simsummary.rgr.agreesummary.rgr.wabawaba

Dependencies:latticeMASSnlme

Citation

To cite package ‘multilevel’ in publications use:

Bliese P (2022). multilevel: Multilevel Functions. R package version 2.7, https://CRAN.R-project.org/package=multilevel.

Corresponding BibTeX entry: 

  @Manual{,
    title = {multilevel: Multilevel Functions},
    author = {Paul Bliese},
    year = {2022},
    note = {R package version 2.7},
    url = {https://CRAN.R-project.org/package=multilevel},
  }

Readme and manuals

Help Manual

Help pageTopics
Average deviation around mean or medianad.m
Simulate significance of average deviation around mean or medianad.m.sim
Brown and Hauenstein (2005) awg agreement indexawg
Data from Bliese and Halverson (1996)bh1996
Data from Bliese, Halverson and Rothberg (2000)bhr2000
Bootstrap ICC values in 2-level databoot.icc
Data from Chen (2005)chen2005
Small nested cohesion data framecohesion
Estimate whether two independent correlations differcordif
Estimate whether two dependent correlations differcordif.dep
Estimate Cronbach's Alphacronbach
Create Coding Matrix for Discontinuous Growth Modeldgm.code
Group Mean Reliability from an lme model (nlme package)gmeanrel
Graph Random Group versus Actual Group distributionsgraph.ran.mean
Estimate Intraclass Correlation Coefficient 1 or ICC(1) from an aov modelICC1
Intraclass Correlation Coefficient 2 or ICC(2) from an aov modelICC2
Item-total correlationsitem.total
Data from Klein, Bliese, Kozlowski et al., (2000)klein2000
Data used in special issue of Leadership Quarterly, Vol. 13, 2002lq2002
Convert data from multivariate to univariate formmake.univ
Randomly mix grouped datamix.data
Multiple ICCs from a datasetmult.icc
Convert two or more variables from multivariate to univariate formmult.make.univ
Firm-Level Panel Data from Donald J. (DJ) Schepkerpaneldat
S3 method for class 'agree.sim'quantile.agree.sim
S3 method for class 'disagree.sim'quantile.disagree.sim
S3 method for class 'rgr.waba'quantile.rgr.waba
Randomly mix grouped data and return function resultsran.group
Random Group Resampling for Within-group Agreementrgr.agree
Random Group Resampling OLS Regressionrgr.ols
Random Group Resampling of Covariance Theorem Decompositionrgr.waba
Remove blanks spaces from non-numeric variables imported from SPSS dataframesrmv.blanks
Conducts an r to z transformationrtoz
James et al., (1984) agreement index for single item measuresrwg
James et al., (1984) agreement index for multi-item scalesrwg.j
Lindell et al. r*wg(j) agreement index for multi-item scalesrwg.j.lindell
Simulate rwg(j) values from a random null distributionrwg.j.sim
Simulate rwg values from a random null distributionrwg.sim
Generate a Sample that Correlates a Given Vectorsam.cor
Sherif (1935) group data from 3 person teamssherifdat
Simulate 2-level ICC(1) values with and without level-1 correlationsim.icc
Simulate a multilevel correlationsim.mlcor
Simulate Standard Error Bias in Non-Independent Datasimbias
Estimate Sobel's (1982) Test for Mediationsobel
S3 method for class 'agree.sim'summary.agree.sim
S3 method for class 'disagree.sim'summary.disagree.sim
S3 method for class 'rgr.agree'summary.rgr.agree
S3 method for class 'rgr.waba'summary.rgr.waba
Tank data from Bliese and Lang (2016)tankdat
Data from Bliese and Ployhart (2002)univbct
Covariance Theoreom Decomposition of Bivariate Two-Level Correlationwaba