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Papers: 10.1371/journal.pone.0231500

https://doi.org/10.1371/journal.pone.0231500

Propensity score adjustment using machine learning classification algorithms to control selection bias in online surveys

Cited by: 23
Author(s): Ramón Ferri‐García, María del Mar Rueda
Published: over 6 years ago

Software Mentions 12

cran: C50
C5.0 Decision Trees and Rule-Based Models
Papers that mentioned: 15
Very Likely Science (99)
cran: e1071
Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien
Papers that mentioned: 419
Very Likely Science (85)
cran: gbm
Generalized Boosted Regression Models
Papers that mentioned: 250
Very Likely Science (100)
cran: ggplot2
Create Elegant Data Visualisations Using the Grammar of Graphics
Papers that mentioned: 11,441
Very Likely Science (100)
cran: gridExtra
Miscellaneous Functions for "Grid" Graphics
Papers that mentioned: 298
Very Likely Science (85)
cran: randomForest
Breiman and Cutler's Random Forests for Classification and Regression
Papers that mentioned: 1,447
Very Likely Science (100)
cran: RColorBrewer
ColorBrewer Palettes
Papers that mentioned: 490
Very Likely Science (83)
cran: rpart
Recursive Partitioning and Regression Trees
Papers that mentioned: 431
Very Likely Science (100)
cran: RWeka
R/Weka Interface
Papers that mentioned: 50
Very Likely Science (75)
cran: xlsx
Read, Write, Format Excel 2007 and Excel 97/2000/XP/2003 Files
Papers that mentioned: 95
Very Likely Science (75)
pypi: gbm
Read and analyze GBM data
Papers that mentioned: 250
Very Likely Science (100)
pypi: xlsx
XLSX Parsing (from js-xlsx)
Papers that mentioned: 95
Very Likely Science (65)