Penalized Spline Nonparametric Mixed Models for Inference About a Finite Population Mean from Two-Stage Samples
By Hui Zheng, Roderick J. A. Little. 2003
57 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/f46c4c6ca31e5f094124f926625c72a163527269
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Maria Giovanna Ranalli
- Roderick J. A. Little
- Paul T. von Hippel
- Victoria Savalei
- Donald B. Rubin
- Craig K. Enders
- Toke S. Aidt
- S. van Buuren
Citations in the corpus
- Non‐parametric small area estimation using penalized spline regression (2008, methodology): “In the survey context, Zheng and Little (2004) proposed a model-based estimator for cluster sampling, in which the regression model combines a spline model with a random effect for the clusters.”
- Model-assisted estimation for complex surveys using penalised splines (2005, background): “Recently, Zheng and Little (2003) have proposed a model-based survey estimator that uses penalized splines to account for the effect of non-ignorable design weights, and have extended it to the case of two-stage sampling in Zheng and Little (2004).”
- Nonparametric small area estimation using penalized spline regression (2005, unknown): “In the survey context , Zheng and Little (2003) propose a model-based estimator for cluster sampling, in which the regression model combines a spline model with a random effect for the clusters.”
- To Model or Not To Model? Competing Modes of Inference for Finite Population Sampling (2004, methodology): “(For more details and additional simulation results, see Zheng and Little 2003, 2004a.) Generalizations of this approach to two-stage sampling have been considered by Zheng and Little (2004b).”
- Inference for the Population Total from Probability-Proportional-to-Size Samples Based on Predictions from a Penalized Spline Nonparametric Model (2003, unknown): “Another extension of our proposed approach, to multistage sampling, is discussed in Zheng and Little (2004).”
- Calibrated Bayes, an alternative inferential paradigm for official statistics (2012, background): “…by modeling the outcome as a spline function of size, avoids this problem, and has been shown to yield Bayesian inferences with superior frequentist properties to sample-weighted estimates in simulations (Zheng and Little 2004, 2005; Yuan and Little 2007, 2008; Chen, Elliott and Little 2010).”