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1.
library orrh € i}ePf\rtTfli1nt of St~i':F(>; North Carolma State UnwersltyMEASUREMENT ERROR AND CORRECTIONS FOR ATTENUATION IN
Open Access
Title:
library orrh € i}ePf\rtTfli1nt of St~i':F(>; North Carolma State UnwersltyMEASUREMENT ERROR AND CORRECTIONS FOR ATTENUATION IN
Author:
R. J. Carroll
;
L. A. Stefanski
;
R. J. Carroll
;
L. A. Stefanski
;
R. J. Carroll
;
L. A. Stefanski
R. J. Carroll
;
L. A. Stefanski
;
R. J. Carroll
;
L. A. Stefanski
;
R. J. Carroll
;
L. A. Stefanski
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MacMahon, et al. (1990) present a metaanalysis of the effect of blood pressure on coronary heart disease, as well as new methods for estimation in measurement error models for the case when a replicate or second measurement is made of the fallible predictor. The correction for attenuation used by these authors is compared to others already exis...
MacMahon, et al. (1990) present a metaanalysis of the effect of blood pressure on coronary heart disease, as well as new methods for estimation in measurement error models for the case when a replicate or second measurement is made of the fallible predictor. The correction for attenuation used by these authors is compared to others already existing in the literature, as well as to a new instrumental variable method. The assumptions justifying the various methods are examined and their efficiencies are studied via simulation. Compared to the methods we discuss, that of MacMahon, et al. (1990) may have substantial bias in some circumstances because it does not take into account: (i) possible correlations among the predictors within a study; (ii) possible bias in the second measurement; or (iii) possibly differing marginal distributions of the predictors and/or measurement errors across studies
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Year of Publication:
20100227
Source:
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS_1992_2222.pdf
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS_1992_2222.pdf
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en
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310 Collections of general statistics
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.4276
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS_1992_2222.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.4276
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS_1992_2222.pdf
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2.
Transformations in Regression: A Robust Analysis
Open Access
Title:
Transformations in Regression: A Robust Analysis
Author:
R. J. Carroll
R. J. Carroll
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The Pennsylvania State University CiteSeerX Archives
Year of Publication:
20100920
Source:
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1544.pdf
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1544.pdf
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Subjects:
Power transfonnations ; BoxCox model ; robust estimation ; influence functions ; bounded influence ; likelihoodraLiotype tests
Power transfonnations ; BoxCox model ; robust estimation ; influence functions ; bounded influence ; likelihoodraLiotype tests
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.5265
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1544.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.5265
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1544.pdf
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3.
ON PREDICTION AND THE POWER TRANSPORMATION FAMILY
Open Access
Title:
ON PREDICTION AND THE POWER TRANSPORMATION FAMILY
Author:
R. J. Carroll
R. J. Carroll
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The power transformation family studied by Box and Cox (1964) for transforming to a normal linear model has recently been further studied by Bickel and Doksum (1978), who show that "the cost of not knowing Aand estimating it. is generally severe"; some of the variances for regression parameters can be extremely large. We consider prediction of f...
The power transformation family studied by Box and Cox (1964) for transforming to a normal linear model has recently been further studied by Bickel and Doksum (1978), who show that "the cost of not knowing Aand estimating it. is generally severe"; some of the variances for regression parameters can be extremely large. We consider prediction of future observations (untransformed) when the data can be transfo~ed to a linear model and show that while there is a cost due to estimating A it is generally not severe. Similar results emerge for the two sample problems. MonteCarlo results lend credence to the asymptotic calculations. Key Words and Phrases:
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Year of Publication:
20100224
Source:
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1264.pdf
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1264.pdf
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text
Language:
en
Subjects:
Power transformations ; Prediction ; Robustness ; BoxCox family ; Asymptotic theory
Power transformations ; Prediction ; Robustness ; BoxCox family ; Asymptotic theory
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.153.9694
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1264.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.153.9694
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1264.pdf
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4.
A comparison between maximum likelihood and generalized least squares in a heteroscedastic model
Open Access
Title:
A comparison between maximum likelihood and generalized least squares in a heteroscedastic model
Author:
R. J. Carroll
R. J. Carroll
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by
by
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Year of Publication:
20100227
Source:
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1334.pdf
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1334.pdf
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.7401
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1334.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.7401
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1334.pdf
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5.
Robust estimation in heteroscedastic linear models when there are many parameters
Open Access
Title:
Robust estimation in heteroscedastic linear models when there are many parameters
Author:
R. J. Carroll
R. J. Carroll
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We study estiuultion of regression parameters in heteroscedastic linear models when the number of parameters is large. The results
We study estiuultion of regression parameters in heteroscedastic linear models when the number of parameters is large. The results
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Year of Publication:
20100920
Source:
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1321.pdf
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1321.pdf
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text
Language:
en
Subjects:
Key Words and Phrases ; Iieteroscedasticity ; Linear MOdels ; Regression ; Weighted Least Squares ; Robustness
Key Words and Phrases ; Iieteroscedasticity ; Linear MOdels ; Regression ; Weighted Least Squares ; Robustness
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.7768
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1321.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.7768
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1321.pdf
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6.
Diagnostics and Robust Estimation When Transforming the Regression Model and the Response
Open Access
Title:
Diagnostics and Robust Estimation When Transforming the Regression Model and the Response
Author:
R. J. Carroll
R. J. Carroll
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In regression analysis, the response is often transformed to remove heteroscedasticity and/or skewness. When a model already exists for the untransformedresponse, then it can be preserved by transforming both the model and the response with the same transformation. This methodology, which we call II transform both sides II has been appl ied in s...
In regression analysis, the response is often transformed to remove heteroscedasticity and/or skewness. When a model already exists for the untransformedresponse, then it can be preserved by transforming both the model and the response with the same transformation. This methodology, which we call II transform both sides II has been appl ied in several recent papers, and appears highly useful in practice. When a • parametric transformation family such as power transformations is used, ~en the transformation can be estimated by maximum likelihood. The MLE however is very sensitive to outliers. In this article, we propose 2 diagnostics which indicate cases influential for the transformation or e regression parameters. We also propose a robust boundedinfluence estimator similar to the KraskerWelsch regression estimate. Both the diagnostics and the robust estimator can be implemented on standard software. 4 1.
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Year of Publication:
20100227
Source:
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1592.pdf
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1592.pdf
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Language:
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DDC:
519 Probabilities & applied mathematics
(computed)
;
310 Collections of general statistics
(computed)
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.6550
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1592.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.6550
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS__1592.pdf
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7.
Abstract:
Open Access
Title:
Abstract:
Author:
R. J. Carroll
R. J. Carroll
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Description:
In regre~sion.~1¥_~.~",.:te~.!~rS.2~sl!_1. §. often transformed to remove heteroscedastiGlty~:o'''''''~n'a model already exists I. for the untransformed respBiise;"'thei\""'lt"!cari ~ ~ preserved by applying the i. ~ ·'~c~'<~·",:,:::.';"••~,~:,~.:. same transform to both the model and the response. This methodology, _.',,_ _ '~'~_"""~_~I"...
In regre~sion.~1¥_~.~",.:te~.!~rS.2~sl!_1. §. often transformed to remove heteroscedastiGlty~:o'''''''~n'a model already exists I. for the untransformed respBiise;"'thei\""'lt"!cari ~ ~ preserved by applying the i. ~ ·'~c~'<~·",:,:::.';"••~,~:,~.:. same transform to both the model and the response. This methodology, _.',,_ _ '~'~_"""~_~I"'''''''" '.".,::: ":" '.::.:._ _ c Iwhich we call "transforJl.brth.s,.ides~.QiUt been applied in several recent papers, and appears highly useful in practice. When a parametric transformation family such as the power transformations is used, then the transformation can be estimated by maximum likelihood. The MLE, however, is very sensitive to outliers. In this article, we propose diagnostics to indicate cases influential for the transformation orPage 2 regression parameters. We also propose a robust boundedinfluence estimator similar to the KraskerWelsch regression estimator. Acknowledge.ent
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20100227
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http://www.stat.ncsu.edu/library/mimeo.archive/ISMS_1986_1706.pdf
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS_1986_1706.pdf
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.8023
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS_1986_1706.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.8023
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS_1986_1706.pdf
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8.
NAME DATE • METAANALYSIS, MEASUREMENT ERROR AND CORRECTIONS FOR ATTENUATION
Open Access
Title:
NAME DATE • METAANALYSIS, MEASUREMENT ERROR AND CORRECTIONS FOR ATTENUATION
Author:
R. J. Carroll
;
L. A. Stefanski
;
R. J. Carroll
;
L. A. Stefanski
R. J. Carroll
;
L. A. Stefanski
;
R. J. Carroll
;
L. A. Stefanski
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Description:
MacMahon, et al. (1990) present a metaanalysis of the effect of blood pressure on coronary heart disease, as well as new methods for estimation in measurement error models for the case when a replicate or second measurement is made of the fallible predictor. The correction for attenuation used by these authors is compared to others already exis...
MacMahon, et al. (1990) present a metaanalysis of the effect of blood pressure on coronary heart disease, as well as new methods for estimation in measurement error models for the case when a replicate or second measurement is made of the fallible predictor. The correction for attenuation used by these authors is compared to others already existing in the literature, as well as to a new instrumental variable method. The assumptions justifying the various methods are examined and their efficiencies are studied via simulation. Compared to the methods we discuss, that of MacMahon, et al. (1990) may have substantial bias in some circumstances because it does not take into account: (i) possible correlations among the predictors within a study; (ii) possible bias in the second measurement; or (iii) possibly differing marginal distributions of the predictors across studies
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20100227
Source:
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS_1991_2201.pdf
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS_1991_2201.pdf
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.5195
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS_1991_2201.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.5195
http://www.stat.ncsu.edu/library/mimeo.archive/ISMS_1991_2201.pdf
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9.
Nonparametric Estimation Via Local Estimating Equations, With Applications To Nutrition Calibration
Open Access
Title:
Nonparametric Estimation Via Local Estimating Equations, With Applications To Nutrition Calibration
Author:
Carroll David Ruppert
;
R. J. Carroll
;
A. H. Welsh
Carroll David Ruppert
;
R. J. Carroll
;
A. H. Welsh
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Description:
Estimating equations have found wide popularity recently in parametric problems, yielding consistent estimators with asymptotically valid inferences obtained via the sandwich formula. Motivated by a problem in nutritional epidemiology, we use estimating equations to derive nonparametric estimators of a "parameter" depending on a predictor. The n...
Estimating equations have found wide popularity recently in parametric problems, yielding consistent estimators with asymptotically valid inferences obtained via the sandwich formula. Motivated by a problem in nutritional epidemiology, we use estimating equations to derive nonparametric estimators of a "parameter" depending on a predictor. The nonparametric component is estimated via local polynomials with loess or kernel weighting; asymptotic theory is derived for the latter. In keeping with the estimating equation paradigm, variances of the nonparametric function estimate are estimated using the sandwich method, in an automatic fashion, without the need typical in the literature to derive asymptotic formulae and plugin an estimate of a density function. The same philosophy is used in estimating the bias of the nonparametric function, i.e., we use an empirical method without deriving asymptotic theory on a casebycase basis. The methods are applied to a series of examples. The appli.
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Year of Publication:
20090413
Source:
ftp://ftp.orie.cornell.edu/pub/techreps/TR1168.ps
ftp://ftp.orie.cornell.edu/pub/techreps/TR1168.ps
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.7.2925
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10.
STATISTICS IN MEDICINE Statist. Med. 2004; 00:1–24 Simple fitting of subjectspecific curves for longitudinal data
Open Access
Title:
STATISTICS IN MEDICINE Statist. Med. 2004; 00:1–24 Simple fitting of subjectspecific curves for longitudinal data
Author:
M. Durbán
;
J. Harezlak
;
R. J. Carroll
M. Durbán
;
J. Harezlak
;
R. J. Carroll
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Description:
We present a simple semiparametric model for fitting subjectspecific curves for longitudinal data. Individual curves are modeled as penalized splines with random coefficients. This model has a mixed model representation, and it is easily implemented in standard statistical software. We conduct an analysis of the longterm effect of radiation th...
We present a simple semiparametric model for fitting subjectspecific curves for longitudinal data. Individual curves are modeled as penalized splines with random coefficients. This model has a mixed model representation, and it is easily implemented in standard statistical software. We conduct an analysis of the longterm effect of radiation therapy on the height of children suffering from acute lymphoblastic leukemia using penalized splines in the framework of semiparametric mixed effects models. The analysis revealed significant differences between therapies and showed that the growth rate of girls in the study cannot be fully explained by the groupaverage curve and that individual curves are necessary to reflect the individual response to treatment. We also showhowto implement these models in SPLUS and R in the appendix. Copyright c ○ 2004 John Wiley & Sons, Ltd.
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20130817
Source:
http://www.stat.tamu.edu/~
carroll
/ftp/2004.papers.directory/durban_final.pdf
http://www.stat.tamu.edu/~
carroll
/ftp/2004.papers.directory/durban_final.pdf
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Subjects:
key words ; Linear mixed models ; Restricted likelihood ratio tests ; Penalized splines ; Acute
key words ; Linear mixed models ; Restricted likelihood ratio tests ; Penalized splines ; Acute
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.329.3596
http://www.stat.tamu.edu/~carroll/ftp/2004.papers.directory/durban_final.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.329.3596
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(1,824) Zalewski, P
(1,823) Hrubec, J
(1,792) Gokieli, R
(1,773) Krammer, M
(1,752) Mulders, M
(1,749) Neumeister, N
(1,725) Tsirou, A
(1,714) Marco, R
(1,713) Della Ricca, G
(1,698) Pol, ME
(1,696) Siegrist, P
(1,670) Cavallo, FR
(1,657) Adzic, P
(1,655) Benvenuti, AC
(1,651) Lethuillier, M
(1,646) Navarria, FL
(1,646) Paganini, P
(1,639) Besancon, M
(1,605) Glege, F
(1,593) Pernicka, M
(1,557) Gele, D
(1,537) Chen, M
(1,535) De Boer, W
(1,522) Bloch, D.
(1,522) Doroba, K.
(1,521) Adam, W.
(1,519) Camporesi, T.
(1,518) Baillon, P.
(1,518) Czellar, S.
(1,516) Jarry, P.
(1,509) Hrubec, J.
(1,508) Demaria, N.
(1,505) Juillot, P.
(1,502) Feindt, M.
(1,498) Amapane, N
(1,482) Gorski, M
(1,478) Treille, D.
(1,477) Loukas, D.
(1,477) Marco, J.
(1,477) Markou, A.
(1,475) Checchia, P.
(1,474) Pape, L.
(1,474) Ragazzi, S.
(1,474) Romero, A.
(1,472) Rovelli, T.
(1,469) Simonetto, F.
(1,464) Margoni, M.
(1,464) Ronchese, P.
(1,464) Strauss, J.
(1,463) Torassa, E
(1,460) Perrotta, A.
(1,455) Liko, D.
(1,455) Matorras, F.
(1,450) Zalewski, P.
(1,444) Krammer, M.
(1,443) Mazzucato, M
(1,440) Paganoni, M.
(1,433) Vlasov, E.
(1,432) Mirabito, L.
(1,427) Cossutti, F.
(1,419) Voutilainen, M
(1,414) Chierici, R.
(1,411) Mariotti, C.
Author:
Subject
(651) particle physics experiment
(578) physics
(530) hadron hadron scattering
(375) cms
(238) experiment hep
(167) phys hexp physics high energy physics experiment
(138) lhc
(135) multidisciplinary
(130) article
(128) research article
(125) info eu repo classification ddc 530
(108) particles fields
(76) hep ex
(67) cern lhc coll
(67) qcd
(66) supersymmetry
(63) experimental results
(62) large detector systems for particle and...
(59) lund monte carlo
(58) experiment nucl
(58) p p scattering
(56) cms collaboration
(53) detectors and experimental techniques
(53) lep
(53) qc physics
(52) standard model
(51) jet fragmentation
(51) nuclear physics
(49) e e annihilation
(48) cell parameters
(48) crystal structure
(48) crystal system
(48) experimental 3d coordinates
(48) space group
(44) cross section
(43) decays
(39) centre of mass
(39) humans
(38) energies
(38) higgs
(35) articles
(34) model
(34) monte carlo
(34) radiative corrections
(33) collisions
(32) data collection
(32) female
(31) detector
(31) nuclear physics experiment
(30) events
(30) particles
(30) top quark
(29) 8000 gev cms
(29) heavy ion collisions
(29) heavy ions
(27) confidence level
(27) mass
(26) charged particles
(25) calorimeters
(24) annihilation
(23) collaboration
(23) general physics
(23) higgs boson
(23) quark gluon plasma
(22) collider
(22) hadron colliders
(21) 7000 gev cms
(21) e e collisions
(21) male
(21) science technology
(21) top physics
(20) exotica
(20) info eu repo classification ddc 550
(20) jet bottom
(20) p p over bar collisions
(20) particle tracking detectors gaseous detectors
(20) tellurium compounds
(19) delphi detector
(19) distributions
(19) monte carlo simulation
(19) muon spectrometers
(19) phys phys phys ins det physics physics...
(19) search
(18) decay
(18) jets
(17) background
(17) bhabha scattering
(17) boson
(17) colliders
(17) e e physics
(17) energy
(17) fragmentation
(17) integrated luminosity
(17) medical and health sciences
(17) mssm
(17) performance of high energy physics detectors
(17) perspective
(17) physics and astronomy
(17) proton proton collisions
(17) resonance
Subject:
Dewey Decimal Classification (DDC)
(950) Physics [53*]
(219) Medicine & health [61*]
(118) Astronomy [52*]
(107) Life sciences; biology [57*]
(53) Chemistry [54*]
(50) Statistics [31*]
(39) History of Europe [94*]
(33) Computer science, knowledge & systems [00*]
(28) Economics [33*]
(28) Engineering [62*]
(21) Agriculture [63*]
(20) Library & information sciences [02*]
(16) Psychology [15*]
(16) Plants (Botany) [58*]
(15) Mathematics [51*]
(14) Technology [60*]
(13) Social problems & social services [36*]
(13) Animals (Zoology) [59*]
(12) Science [50*]
(10) Social sciences, sociology & anthropology...
(10) Earth sciences & geology [55*]
(10) Sports, games & entertainment [79*]
(8) Political science [32*]
(7) Other religions [29*]
(7) Chemical engineering [66*]
(6) Management & public relations [65*]
(6) Arts [70*]
(5) Education [37*]
(3) Commerce, communications & transportation...
(3) Manufacturing [67*]
(3) Geography & travel [91*]
(2) Metaphysics [11*]
(2) Public administration & military science [35*]
(2) Language [40*]
(2) Linguistics [41*]
(2) English & Old English languages [42*]
(1) Magazines, journals & serials [05*]
(1) Philosophy [10*]
(1) Logic [16*]
(1) Ethics [17*]
(1) Modern western philosophy [19*]
(1) Christianity & Christian theology [23*]
(1) Law [34*]
(1) Customs, etiquette & folklore [39*]
(1) Landscaping & area planning [71*]
(1) History [90*]
(1) History of ancient world (to ca. 499)...
Dewey Decimal Classification (DDC):
Year of Publication
(1,290) 2013
(863) 2012
(852) 2010
(811) 2011
(667) 2014
(262) 2000
(253) 2001
(217) 1996
(201) 1999
(191) 1995
(173) 1998
(171) 2009
(157) 1997
(121) 2004
(120) 1994
(110) 2002
(110) 2008
(108) 1993
(96) 1992
(81) 2003
(76) 2006
(71) 1990
(70) 1991
(70) 2005
(63) 2007
(54) 2015
(23) 1983
(21) 1982
(16) 1979
(15) 1987
(14) 1984
(14) 1989
(11) 1988
(9) 1956
(9) 1980
(8) 1981
(8) 1985
(8) 1986
(7) 1978
(6) 1954
(6) 1969
(5) 1955
(5) 1967
(5) 1968
(5) 1970
(5) 1974
(5) 1977
(4) 1973
(3) 1962
(2) 1924
(2) 1960
(2) 1963
(2) 1965
(2) 1971
(2) 1975
(1) 1891
(1) 1922
(1) 1930
(1) 1934
(1) 1936
(1) 1937
(1) 1945
(1) 1947
(1) 1948
(1) 1951
(1) 1952
(1) 1957
(1) 1959
(1) 1972
Year of Publication:
Content Provider
(760) CERN (Switzerland)
(748) Oxford Univ.: Research Archive (ORA)
(587) São Paulo UNESP: Repository
(531) Athens National Technical Univ.: DSpace
(516) Joint Inst. for Nuclear Research: JINR Document...
(411) PubMed Central
(375) STFC (United Kingdom)
(336) London Brunel Univ.: Research Archive (BURA)
(333) Aachen RWTH: Publications
(304) Ghent Univ.
(237) London Univ. College: UCL Discovery
(215) DESY Hamburg
(182) HAL  Hyper Article en Ligne
(147) Springer Open Choice
(144) CiteSeerX
(116) National Central Univ. (Taiwan): Repository
(100) Queensland Univ.: UQ eSpace
(95) HighWire Press
(92) DataCite Metadata Store
(81) UMass Amherst
(67) Purdue Univ.: ePubs
(66) OSTI DOE (USA)
(63) Glasgow Univ.
(54) Manchester Univ.: eScholar Services
(53) Wollongong Univ.
(50) ArXiv.org
(40) Inst. Nat. Fisica Nucleare (INFN): OA Repository
(39) Karlsruhe Univ.: Scientific Articles Repository
(29) London King's College: Research Portal
(25) North Texas Univ.: The Portal to Texas History
(24) DOAJ Articles
(23) California Univ.: eScholarship
(22) Strathclyde Univ.
(20) London Imperial Coll.
(18) Tasmania Univ.: eCite
(16) Belfast Queen's Univ.: Research Portal
(16) Surrey Univ.
(15) Swinburne Univ. of Technology: Research Bank
(14) Pittsburgh Univ.: DScholarship@Pitt
(13) Lund Univ. Publications (LUP)
(13) Cardiff Univ.:ORCA
(12) RePEc.org
(12) Michigan Univ.: Deep Blue
(11) BioMed Central
(11) Lenus (Irish Health Publications Archive)
(11) Sydney Macquarie Univ.: ResearchOnline
(11) Leuven KU: Lirias
(11) Massachusetts Univ., Medical School: eScholarship
(11) Pittsburgh Univ.: Electronic Theses &...
(9) NASA Technical Reports Server (NTRS)
(9) Southampton Univ.: ePrints Soton
(9) Texas A&M Univ.: Digital Repository
(8) NERC (United Kingdom)
(8) Newcastle Univ. (Australia)
(8) Utah State Univ.: DigitalCommons
(7) Caltech: Authors
(7) Iowa State Univ.: Digital Repository
(7) Jackson Laboratory (JAX): Mouseion
(7) Royal Melbourne Inst. of Tech. (RMIT)
(7) Lancester Univ.
(7) East Anglia Univ.: Digital Repository
(7) Milan Univ.: Archivio Istituzionale della Ricerca
(7) Notre Dame Univ. (Australia)
(7) Warwick Univ.: Warwick Research Archive Portal
(6) Christie School of Oncology: Repository
(6) Project Euclid
(6) Griffith Univ.
(6) Harvard Univ.: DASH
(6) Lausanne Ecole Polytechnique Fed.: Infoscience
(6) Birmingham Univ.: ePrints
(6) Adelaide Univ.: Digital Library
(6) Coimbra Univ.: Estudo Geral
(5) USDA NAL (USA)
(5) Jülich Forschungszentrum: JuSER
(5) Georgia Tech: SMARTech
(5) White Rose Univ. Cons.
(5) Auckland Univ.
(5) Bern Univ.: BORIS
(4) Cornell Univ.: eCommons
(4) Cold Spring Harbor Lab: Repository
(4) Deakin Univ.: Deakin Research Online
(4) Hindawi Publishing Corporation
(4) Liège Univ.: ORBi
(4) Bochum Univ. (RUB): Campus Research Bibliography
(4) Dundee Univ.: Online Publications
(4) Illinois Univ.: Archives
(4) Illinois Univ.: INDIGO
(4) Illinois Digital Environment for Access to...
(4) Nijmegen Univ.
(4) Sussex Univ.
(4) Zurich Univ.: ZORA
(3) Biodiversty Heritage Library (BHL)
(3) Central Queensland Univ: aCQUIRe
(3) DUMAS (France)
(3) Illinois Digital Archives
(3) LSHTM: Research Online
(3) MaxDelbrueckCenter for Molecular Medicin (MDC)
(3) CCSD: memSIC
(3) India NorthEastern Hill Univ.: NEHU Digital...
(3) Queensland Univ. Tech.: QUT ePrints
Content Provider:
Language
(4,494) English
(3,025) Unknown
(1) Chinese
Language:
Document Type
(3,796) Article, Journals
(2,033) Unknown
(1,509) Text
(131) Reports, Papers, Lectures
(24) Books
(15) Primary Data
(5) Theses
(4) Maps
(1) Audio
(1) Images
Document Type:
Access
(6,093) Unknown
(1,426) Open Access
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