Package: amen 1.4.4
amen: Additive and Multiplicative Effects Models for Networks and Relational Data
Analysis of dyadic network and relational data using additive and multiplicative effects (AME) models. The basic model includes regression terms, the covariance structure of the social relations model (Warner, Kenny and Stoto (1979) <doi:10.1037/0022-3514.37.10.1742>, Wong (1982) <doi:10.2307/2287296>), and multiplicative factor models (Hoff(2009) <doi:10.1007/s10588-008-9040-4>). Several different link functions accommodate different relational data structures, including binary/network data, normal relational data, zero-inflated positive outcomes using a tobit model, ordinal relational data and data from fixed-rank nomination schemes. Several of these link functions are discussed in Hoff, Fosdick, Volfovsky and Stovel (2013) <doi:10.1017/nws.2013.17>. Development of this software was supported in part by NIH grant R01HD067509.
Authors:
amen_1.4.4.tar.gz
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amen.pdf |amen.html✨
amen/json (API)
NEWS
| # Install 'amen' in R: |
| install.packages('amen', repos = c('https://pdhoff.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/pdhoff/amen/issues
- IR90s - International relations in the 90s
- YX_bin - Binary relational data and covariates
- YX_bin_long - Binary relational data and covariates
- YX_cbin - Censored binary nomination data and covariates
- YX_frn - Fixed rank nomination data and covariates
- YX_nrm - Normal relational data and covariates
- YX_ord - Ordinal relational data and covariates
- YX_rrl - Row-specific ordinal relational data and covariates
- addhealthc3 - AddHealth community 3 data
- addhealthc9 - AddHealth community 9 data
- coldwar - Cold War data
- comtrade - Comtrade data
- dutchcollege - Dutch college data
- lazegalaw - Lazega's law firm data
- sampsonmonks - Sampson's monastery data
- sheep - Sheep dominance data
Last updated 4 years agofrom:aa6ca84d04. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 09 2024 |
| R-4.5-win | NOTE | Nov 09 2024 |
| R-4.5-linux | NOTE | Nov 09 2024 |
| R-4.4-win | NOTE | Nov 09 2024 |
| R-4.4-mac | NOTE | Nov 09 2024 |
| R-4.3-win | NOTE | Nov 09 2024 |
| R-4.3-mac | NOTE | Nov 09 2024 |
Exports:addlinesameame_repcircplotdesign_arrayel2smgofstatsldZgbmellsrmRhomhalfnetplotprecomputeXraSab_bin_fcraSab_cbin_fcraSab_frn_fcrbeta_ab_fcrbeta_ab_rep_fcrmvnormrrho_fcrrho_mhrrho_mh_reprs2_fcrs2_rep_fcrSab_fcrSuv_fcrUV_fcrUV_rep_fcrUV_sym_fcrwishrZ_bin_fcrZ_cbin_fcrZ_frn_fcrZ_nrm_fcrZ_ord_fcrZ_rrl_fcrZ_tob_fcsimY_binsimY_frnsimY_nrmsimY_ordsimY_rrlsimY_tobsimZsm2elXbetaxnetzscores
Dependencies:
DIY modeling of a binary network outcome
Rendered fromdiy_binary_demo.Rmdusingknitr::rmarkdownon Nov 09 2024.Last update: 2020-12-07
Started: 2018-07-31
DIY overdispersed Poisson network model
Rendered fromdiy_Poisson_demo.Rmdusingknitr::rmarkdownon Nov 09 2024.Last update: 2020-12-07
Started: 2018-07-31
Modeling a binary network outcome
Rendered frombinary_demo.Rmdusingknitr::rmarkdownon Nov 09 2024.Last update: 2020-12-07
Started: 2018-05-30
