Evaluating machine learning methods for estimation in online surveys with superpopulation modeling

DOI10.1016/j.matcom.2020.03.005OpenAlexW3012966156MaRDI QIDQ1998585

Luis Castro-Martín, Ramón Ferri-García, Maria del Mar Rueda García

Publication date: 6 March 2021

Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10481/68515

zbMATH Keywords

machine learningonline surveys and simulationsuperpopulation modeling

Mathematics Subject Classification ID

Artificial intelligence (68Txx) Design of statistical experiments (62Kxx) Nonparametric inference (62Gxx)

Related Items (2)

Comments on: ``Deville and Särndal's calibration: revisiting a 25 years old successful optimization problem ⋮ Variable selection in propensity score adjustment to mitigate selection bias in online surveys

Uses Software

• R
• lme4
• caret
• Lmertest
• MuMIn

Cites Work

• Unnamed Item
• Model-assisted survey estimation with modern prediction techniques
• Inference for nonprobability samples
• The Bayesian Lasso
• The central role of the propensity score in observational studies for causal effects
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Comparing Inference Methods for Non‐probability Samples

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