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	Provedor de dados AgEcon (4) Scientia Agricola (1) Autor Hardouin, Jean-Benoit (1) Lara,Idemauro Antonio Rodrigues de (1) Leonard, Mary (1) McDowell, Allen (1) Menarin,Vinícius (1) Ratcliffe, Sarah J. (1) Shults, Justine (1) Silva,Sila Carneiro da (1) Stillman, Steven (1) Mais... Palavra-chave Generalized estimating equations (5) Research Methods/ Statistical Methods (4) Andersen Z test (1) Clustered data (1) Conditional maximum likelihood method (1) Correlated data (1) Fit tests (1) Generalized linear models (1) Item characteristics curves (1) Item response theory (1) Local odds ratio (1) Longitudinal data (1) Longitudinal multinomial data (1) Marginal maximum likelihood method (1) Quasi–least squares (1) R1c (1) R1m (1) Rasch model (1) Raschtest (1) SUR (1) Mais... Tipo do documento Article (2) Journal Article (2) Info:eu-repo/semantics/article (1) Ano 2017 (1) 2007 (2) 2004 (1) 2003 (1) País United States (4) Brazil (1) Idioma Inglês (5)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 5 Primeira ... 1 ... Última From the help desk: Seemingly unrelated regression with unbalanced equations AgEcon McDowell, Allen. This article demonstrates how to estimate the parameters of a system of seemingly unrelated regressions when the equations are unbalanced, i.e., when the equations have an unequal number of observations. With estimators that require the data to be in wide format, such as Stata’s sureg, the equations must be balanced. Any additional observations that are available for some equations, but not for all, are discarded, potentially resulting in a loss of efficiency. Reshaping and scaling the data allows us to use Stata’s xtgee command to fit the model and obtain estimates utilizing all the available data. The resulting estimator is potentially more efficient when the equations are unbalanced. Tipo: Journal Article Palavras-chave: SUR; Seemingly unrelated regression; Unbalanced equations; Generalized estimating equations; Research Methods/ Statistical Methods. Ano: 2004 URL: http://purl.umn.edu/116272 Rasch analysis: Estimation and tests with raschtest AgEcon Hardouin, Jean-Benoit. Analyzing latent variables is becoming more and more important in several fields, such as clinical research, psychology, educational sciences, ecology, and epidemiology. The item response theory allows analyzing latent variables measured by questionnaires of items with binary or ordinal responses. The Rasch model is the best known model of this theory for binary responses. Although one can estimate the parameters of the Rasch model with the clogit or xtlogit command (or with the unofficial gllamm command), these commands require special data preparation. The proposed raschtest command easily allows estimating the parameters of the Rasch model and fitting the resulting model. Tipo: Article Palavras-chave: Raschtest; Rasch model; Generalized estimating equations; Conditional maximum likelihood method; Marginal maximum likelihood method; Andersen Z test; Van den Wollenberg Q1 test; R1c; R1m; Fit tests; Item response theory; U test; Splitting test; Item characteristics curves; Research Methods/ Statistical Methods. Ano: 2007 URL: http://purl.umn.edu/119253 Improved generalized estimating equation analysis via xtqls for quasi–least squares in Stata AgEcon Shults, Justine; Ratcliffe, Sarah J.; Leonard, Mary. Quasi–least squares (QLS) is an alternative method for estimating the correlation parameters within the framework of the generalized estimating equation (GEE) approach for analyzing correlated cross-sectional and longitudinal data. This article summarizes the development of QLS that occurred in several reports and describes its use with the user-written program xtqls in Stata. Also, it demonstrates the following advantages of QLS: (1) QLS allows some correlation structures that have not yet been implemented in the framework of GEE, (2) QLS can be applied as an alternative to GEE if the GEE estimate is infeasible, and (3) QLS uses the same estimating equation for estimation of Β as GEE; as a result, QLS can involve programs already available for GEE. In... Tipo: Article Palavras-chave: Xtqls; Correlated data; Clustered data; Longitudinal data; Generalized estimating equations; Quasi–least squares; Research Methods/ Statistical Methods. Ano: 2007 URL: http://purl.umn.edu/119265 Review of Generalized Estimating Equations by Hardin and Hilbe AgEcon Stillman, Steven. This article reviews Generalized Estimating Equations by Hardin and Hilbe. Tipo: Journal Article Palavras-chave: Generalized estimating equations; Generalized linear models; Research Methods/ Statistical Methods. Ano: 2003 URL: http://purl.umn.edu/116078 Longitudinal model for categorical data applied in an agriculture experiment about elephant grass Scientia Agricola Menarin,Vinícius; Lara,Idemauro Antonio Rodrigues de; Silva,Sila Carneiro da. ABSTRACT Experiments where the response is a categorical variable are usually carried out in many fields such as agriculture. In addition, in some situations this response has three or more levels without an order between them characterizing a multinomial (nominal) response. Statistical models for scenarios where the observations of a nominal response can be considered independent have an extensive literature, such as the baseline-category logit models. However, situations where this assumption is violated (as in longitudinal studies) require specific models that take into consideration the dependence between observations. In this paper, a fairly new extension of the generalized estimating equations is applied to analyze an experiment carried out to... Tipo: Info:eu-repo/semantics/article Palavras-chave: Type of vegetation; Longitudinal multinomial data; Generalized estimating equations; Local odds ratio. Ano: 2017 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162017000400265 Registros recuperados: 5 Primeira ... 1 ... Última

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