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2,116,711
Standard errors:
"... A review and evaluation of standard error estimators using Monte Carlo simulations ..."
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A review and evaluation of standard error estimators using Monte Carlo simulations
Model-Based Analysis of Oligonucleotide Arrays: Model Validation, Design Issues and Standard Error Application
, 2001
"... Background: A model-based analysis of oligonucleotide expression arrays we developed previously uses a probe-sensitivity index to capture the response characteristic of a specific probe pair and calculates model-based expression indexes (MBEI). MBEI has standard error attached to it as a measure of ..."
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Cited by 751 (28 self)
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Background: A model-based analysis of oligonucleotide expression arrays we developed previously uses a probe-sensitivity index to capture the response characteristic of a specific probe pair and calculates model-based expression indexes (MBEI). MBEI has standard error attached to it as a measure
The standard error of equipercentile equating
- Journal of Educational Statistics
, 1982
"... ABSTRACT. The standard error of an equipercentile equating is derived for four situations. Some numerical results are checked by Monte Carlo methods. Numerical standard errors are computed for two sets of real data. Standard errors of linear and equipercentile equating are compared. It is frequently ..."
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Cited by 10 (0 self)
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ABSTRACT. The standard error of an equipercentile equating is derived for four situations. Some numerical results are checked by Monte Carlo methods. Numerical standard errors are computed for two sets of real data. Standard errors of linear and equipercentile equating are compared
Clustered Standard Errors
, 2010
"... “... analyses of group randomized trials that ignore clustering are an exercise in self-deception ” (Cornfield 1978 pg. 101) And, in the ever so enlightening words of Joshua Angrist: “Making a data set larger by copying a smaller one n times generates no new information ” (Angrist and Pischke 2009) ..."
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) Erin Hartman (PS239 Sp2010) Clustered Standard Errors March 10, 2010 2 / 17Clustering in the Modeling World When we use parametric models, what do we usually assume about the errors? Erin Hartman (PS239 Sp2010) Clustered Standard Errors March 10, 2010 3 / 17Clustering in the Modeling World When we use
Robust Standard Errors for Robust Estimators
, 2003
"... A regression estimator is said to be robust if it is still reliable in the presence of outliers. On the other hand, its standard error is said to be robust if it is still reliable when the regression errors are autocorrelated and/or heteroskedastic. This paper shows how robust standard errors can be ..."
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Cited by 15 (2 self)
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A regression estimator is said to be robust if it is still reliable in the presence of outliers. On the other hand, its standard error is said to be robust if it is still reliable when the regression errors are autocorrelated and/or heteroskedastic. This paper shows how robust standard errors can
On the Warnock-Halton quasi-standard error
, 2005
"... This paper investigates an error estimate proposed by Warnock and studied by Halton (2005). That error estimate is simply the sample standard error applied to certain non-randomized quasi-Monte Carlo points. This quasi-standard error (QSE) closely tracks the actual error in an example, and looks to ..."
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Cited by 3 (0 self)
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This paper investigates an error estimate proposed by Warnock and studied by Halton (2005). That error estimate is simply the sample standard error applied to certain non-randomized quasi-Monte Carlo points. This quasi-standard error (QSE) closely tracks the actual error in an example, and looks
the Standard Error of Measurement?
"... Questions and answers about language testing statistics: ..."
Minimum Error Rate Training in Statistical Machine Translation
, 2003
"... Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training cri ..."
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Cited by 663 (7 self)
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Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training criteria which directly optimize translation quality.
Results 1 - 10
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