Results 1  10
of
2,028
Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification
 Psychological Methods
, 1998
"... This study evaluated the sensitivity of maximum likelihood (ML), generalized least squares (GLS), and asymptotic distributionfree (ADF)based fit indices to model misspecification, under conditions that varied sample size and distribution. The effect of violating assumptions of asymptotic robustn ..."
Abstract

Cited by 543 (0 self)
 Add to MetaCart
This study evaluated the sensitivity of maximum likelihood (ML), generalized least squares (GLS), and asymptotic distributionfree (ADF)based fit indices to model misspecification, under conditions that varied sample size and distribution. The effect of violating assumptions of asymptotic
Validation of the ZeroCovariance Assumption in the Error Variance Separation Method of RadarRaingauge Comparisons
"... ABSTRACT: Empirical test of zerocovariance assumption in the error variance separation method is presented. The method had been proposed to filter out ground reference errors in radar rainfall verifications. This investigation uses a large data sample of two 6month periods from the Little Washita ..."
Abstract
 Add to MetaCart
ABSTRACT: Empirical test of zerocovariance assumption in the error variance separation method is presented. The method had been proposed to filter out ground reference errors in radar rainfall verifications. This investigation uses a large data sample of two 6month periods from the Little
Axiomatic quantum field theory in curved spacetime
, 2008
"... The usual formulations of quantum field theory in Minkowski spacetime make crucial use of features—such as Poincare invariance and the existence of a preferred vacuum state—that are very special to Minkowski spacetime. In order to generalize the formulation of quantum field theory to arbitrary globa ..."
Abstract

Cited by 689 (18 self)
 Add to MetaCart
to a fundamental status, and, in essence, all of the properties of the quantum field theory are determined by its OPE. We provide general axioms for the OPE coefficients of a quantum field theory. These include a local and covariance assumption (implying that the quantum field theory is locally
Nonparametric estimation of average treatment effects under exogeneity: a review
 REVIEW OF ECONOMICS AND STATISTICS
, 2004
"... Recently there has been a surge in econometric work focusing on estimating average treatment effects under various sets of assumptions. One strand of this literature has developed methods for estimating average treatment effects for a binary treatment under assumptions variously described as exogen ..."
Abstract

Cited by 630 (25 self)
 Add to MetaCart
as exogeneity, unconfoundedness, or selection on observables. The implication of these assumptions is that systematic (for example, average or distributional) differences in outcomes between treated and control units with the same values for the covariates are attributable to the treatment. Recent analysis has
A Survey on Transfer Learning
"... A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. However, in many realworld applications, this assumption may not hold. For example, we sometimes have a classification task i ..."
Abstract

Cited by 459 (24 self)
 Add to MetaCart
A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. However, in many realworld applications, this assumption may not hold. For example, we sometimes have a classification task
Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance
 Psychological Bulletin
, 1989
"... Addresses issues related to partial measurement in variance using a tutorial approach based on the LISREL confirmatory factor analytic model. Specifically, we demonstrate procedures for (a) using "sensitivity analyses " to establish stable and substantively wellfitting baseline models, (b ..."
Abstract

Cited by 261 (6 self)
 Add to MetaCart
, (b) determining partially invariant measurement parameters, and (c) testing for the invariance of factor covariance and mean structures, given partial measurement invariance. We also show, explicitly, the transformation of parameters from an all^fto an ally model specification, for purposes
Measuring phasesynchrony in brain signals
 Hum. Brain Mapp
, 1999
"... r r Abstract: This article presents, for the first time, a practical method for the direct quantification of frequencyspecific synchronization (i.e., transient phaselocking) between two neuroelectric signals. The motivation for its development is to be able to examine the role of neural synchronie ..."
Abstract

Cited by 346 (6 self)
 Add to MetaCart
synchronies as a putative mechanism for longrange neural integration during cognitive tasks. The method, called phaselocking statistics (PLS), measures the significance of the phase covariance between two signals with a reasonable timeresolution (,100 ms). Unlike the more traditional method of spectral
Consequences of failure to meet assumptions underlying the analysis of variance and covariance
 Review of Educational Research
, 1972
"... The effects of violating the assumptions underlying the fixedeffects analyses of variance (ANOVA) and covariance (ANCOVA) on TypeI and TypeII error rates have been of great concern to researchers and statisticians. The major effects of violation of assumptions are now well known, after nearly fou ..."
Abstract

Cited by 113 (0 self)
 Add to MetaCart
The effects of violating the assumptions underlying the fixedeffects analyses of variance (ANOVA) and covariance (ANCOVA) on TypeI and TypeII error rates have been of great concern to researchers and statisticians. The major effects of violation of assumptions are now well known, after nearly
Consistency of the group lasso and multiple kernel learning
 JOURNAL OF MACHINE LEARNING RESEARCH
, 2007
"... We consider the leastsquare regression problem with regularization by a block 1norm, i.e., a sum of Euclidean norms over spaces of dimensions larger than one. This problem, referred to as the group Lasso, extends the usual regularization by the 1norm where all spaces have dimension one, where it ..."
Abstract

Cited by 274 (33 self)
 Add to MetaCart
it is commonly referred to as the Lasso. In this paper, we study the asymptotic model consistency of the group Lasso. We derive necessary and sufficient conditions for the consistency of group Lasso under practical assumptions, such as model misspecification. When the linear predictors and Euclidean norms
ASSUMPTIONS IN ANALYSIS OF
, 2014
"... assumption also implies that all covariates should be confounding variables, i.e., there are no interactions between group and covariates. ..."
Abstract
 Add to MetaCart
assumption also implies that all covariates should be confounding variables, i.e., there are no interactions between group and covariates.
Results 1  10
of
2,028