Measurement Error Models

By Alexander Kukush. 2011

2,072 citations recorded by the source corpus.

Subfields: Statistics and Probability, Surgery

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

In Surgery

Citations in the corpus

Causal Effect Inference with Deep Latent-Variable Models (2017, neutral): “Consider for example the causal graphs in Figure 1: it’s well known [20, 15, 18, 31, 41] that it is often incorrect to treat the proxies X as if they are ordinary confounders, as this would induce bias.”
Forest Growth and Yield Modeling (2011, methodology): “Correction methods are numerous and covered for linear and nonlinear models in Fuller (1987) and Carroll et al. (2006), respectively.”
Penalized empirical likelihood and growing dimensional general estimating equations (2012, methodology): “…of applications, for example,the pseudo-likelihood approach (Godambe & Heyde, 1987), the instrumental vari bles method in measurement error models (Fuller, 1987) and survey sampling (Fuller, 2009), the generalized method of moments (Hansen, 1982; Hansen & Singleton, 1982) and the generalized…”
Error analysis for circle fitting algorithms (2009, positive): “The geometric ﬁt (which minimizes orthogonal distances) always satisﬁes (29) and attains the lower bound V min ; this was proved by Fuller (Theorem 3.2.1 in [12]) and independently by Chernov and Lesort [8], who named the inequality (40) Kanatani-Cramer-Rao (KCR) lower bound.”
Information bias in health research: definition, pitfalls, and adjustment methods (2016, neutral): “Such results can include inconsistent (or biased) and/or inefficient estimators of regression parameters, which may yield poor inferences about confidence intervals and the hypothesis testing of parameters.(22,34) However, random sampling should not be confused with measurement error variability.”
Text and Causal Inference: A Review of Using Text to Remove Confounding from Causal Estimates (2020, background): “Ideas from the large literature on measurement error models may also be helpful (Fuller, 1987; Carroll et al., 2006; Buonaccorsi, 2010).”
Congenital bone deformities and the inbred wolves (Canis lupus) of Isle Royale (2009, background): “5) is likely robust to these uncertainties, because slopes tend to be steeper than estimatedwhenpredictor variables are measured with error (Fuller, 1987).”
Sparse recovery under matrix uncertainty (2008, neutral): “The Annals of Statistics 2010, Vol. 38, No. 5, 2620–2651 DOI: 10.1214/10-AOS793 © Institute of Mathematical Statistics, 2010”
Are U.S. Cities Underpoliced? Theory and Evidence (2017, methodology): “…mean 0 measurement errors that are mutually uncorrelated and uncorrelated with i, S∗i , and Xi, and i is mean 0 and uncorrelated with S∗i , Xi, ui, and vi. Equations (5) through (7) and the stochastic restrictions just named together constitute the classical measurement error model (Fuller, 1987).”
A climate of uncertainty: accounting for error in climate variables for species distribution models (2015, background): “Accounting for uncertainty in explanatory variables (through what is commonly referred to as measurement error models or errors-in-variables models) is a well-known and important topic in many applied fields, such as engineering and medical studies (Fuller 1987; Carroll et al. 2006).”
Nonparametric Identification and Semiparametric Estimation of Classical Measurement Error Models Without Side Information (2012, background): “A well-known result is that when the function g (x∗) is linear while x∗, x, and y are normal, the model is not identified (see, e.g., Fuller 1987), although the regression coefficients can often be consistently bounded (Klepper and Leamer 1984).”
Lights, Camera … Income! Illuminating the National Accounts-Household Surveys Debate (2016, neutral): “zi,t = γLy L i,t + γGy G i,t + γSy S i,t (26)”
Fast approximate spectral clustering (2009, background): “Data perturbation can be modeled in several different ways, including contaminated distribution models [37], measurement error models [13] and mixture modeling.”