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	Provedor de dados AgEcon (11) Autor Newson, Roger (11) The ALSPAC Study Team (1) Palavra-chave Research Methods/ Statistical Methods (11) Somers' D (3) Confidence interval (2) Confidence intervals (2) Nonparametric methods (2) Propensity score (2) ROC area (2) Rank correlation (2) Rank-sum test (2) Somersd (2) Wilcoxon test (2) ALSPAC (1) Algebraic mean (1) Alpha (1) Arithmetic mean (1) Benjamini (1) Bonferroni (1) Book review (1) Censlope (1) Closed testing procedure (1) Mais... Tipo do documento Journal Article (10) Article (1) Ano 2006 (2) 2005 (1) 2004 (3) 2003 (3) 2002 (1) 2001 (1) Mais... País United States (11) Idioma Inglês (11)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 11 Primeira ... 1 ... Última Review of Generalized Linear Models and Extensions by Hardin and Hilbe AgEcon Newson, Roger. This article reviews Generalized Linear Models and Extensions by Hardin and Hilbe. Tipo: Journal Article Palavras-chave: Generalized linear models; Book review; Research Methods/ Statistical Methods. Ano: 2001 URL: http://purl.umn.edu/115939 Stata tip 13: generate and replace use the current sort order AgEcon Newson, Roger. Tipo: Journal Article Palavras-chave: Research Methods/ Statistical Methods. Ano: 2004 URL: http://purl.umn.edu/116281 Parameters behind “nonparametric” statistics: Kendall's tau, Somers' D and median differences AgEcon Newson, Roger. So-called “nonparametric” statistical methods are often in fact based on population parameters, which can be estimated (with confidence limits) using the corresponding sample statistics. This article reviews the uses of three such parameters, namely Kendall’s τα Somers’ D, and the Hodges–Lehmann median difference. Confidence intervals for these are demonstrated using the somersd package. It is argued that confidence limits for these parameters, and their differences, are more informative than the traditional practice of reporting only p-values. These three parameters are also important in defining other tests and parameters, such as the Wilcoxon test, the area under the receiver operating characteristic (ROC) curve, Harrell’s C, and the Theil median slope. Tipo: Journal Article Palavras-chave: Confidence intervals; Gehan test; Harrell's C; Hodges–Lehmann median difference; Kendall's tau; Nonparametric methods; Rank correlation; Rank-sum test; ROC area; Somers' D; Theil median slope; Wilcoxon test; Research Methods/ Statistical Methods. Ano: 2002 URL: http://purl.umn.edu/115950 Stata tip 1: The eform() option of regress AgEcon Newson, Roger. Tipo: Journal Article Palavras-chave: Research Methods/ Statistical Methods. Ano: 2003 URL: http://purl.umn.edu/116201 Confidence intervals for rank statistics: Somers' D and extensions AgEcon Newson, Roger. Somers’ D is an asymmetric measure of association between two variables, which plays a central role as a parameter behind rank or nonparametric statistical methods. Given predictor variable X and outcome variable Y , we may estimate DYX as a measure of the effect of X on Y , or we may estimate DXY as a performance indicator of X as a predictor of Y. The somersd package allows the estimation of Somers’ D and Kendall’s τα with confidence limits as well as p-values. The Stata 9 version of somersd can estimate extended versions of Somers’ D not previously available, including the Gini index, the parameter tested by the sign test, and extensions to left- or right-censored data. It can also estimate stratified versions of Somers’ D, restricted to pairs in the... Tipo: Journal Article Palavras-chave: Somersd; Somers' D; Kendall's τ_a; Harrell's c; ROC area; Gini index; Population-attributable risk; Rank correlation; Rank-sum test; Wilcoxon test; Sign test; Confidence intervals; Nonparametric methods; Propensity score; Research Methods/ Statistical Methods. Ano: 2006 URL: http://purl.umn.edu/117583 Stata tip 5: Ensuring programs preserve dataset sort order AgEcon Newson, Roger. Tipo: Journal Article Palavras-chave: Research Methods/ Statistical Methods. Ano: 2004 URL: http://purl.umn.edu/116217 Confidence intervals for rank statistics: Percentile slopes, differences, and ratios AgEcon Newson, Roger. I present a program, censlope, for calculating confidence intervals for generalized Theil–Sen median (and other percentile) slopes (and per-unit ratios) of Y with respect to X. The confidence intervals are robust to the possibility that the conditional population distributions of Y , given different values of X, differ in ways other than location, such as having unequal variances. censlope uses the program somersd and is part of the somersd package. censlope can therefore estimate confounder-adjusted percentile slopes, limited to comparisons within strata defined by values of confounders, or by values of a propensity score representing multiple confounders. Iterative numerical methods have been implemented in the Mata language, enabling efficient... Tipo: Article Palavras-chave: Somersd; Censlope; ALSPAC; Robust; Confidence interval; Rank; Nonparametric; Median; Percentile; Slope; Difference; Ratio; Kendall's τ; Somers' D; Theil–Sen; Hodges–Lehmann; Confounder adjusted; Propensity score; Research Methods/ Statistical Methods. Ano: 2006 URL: http://purl.umn.edu/119241 Multiple-test procedures and smile plots AgEcon Newson, Roger; The ALSPAC Study Team. multproc carries out multiple-test procedures, taking as input a list of p-values and an uncorrected critical p-value, and calculating a corrected overall critical p-value for rejection of null hypotheses. These procedures define a confidence region for a set-valued parameter, namely the set of null hypotheses that are true. They aim to control either the family-wise error rate (FWER) or the false discovery rate (FDR) at a level no greater than the uncorrected critical p-value. smileplot calls multproc and then creates a smile plot, with data points corresponding to estimated parameters, the p-values (on a reverse log scale) on the y-axis, and the parameter estimates (or another variable) on the x-axis. There are y-axis reference lines at the uncorrected... Tipo: Journal Article Palavras-chave: Smile plot; Multiple-test procedure; Closed testing procedure; Data mining; Family-wise error rate; False discovery rate; Bonferroni; Sidák; Holm; Holland; Copenhaver; Hochberg; Rom; Simes; Benjamini; Yekutieli; Krieger; Liu; Research Methods/ Statistical Methods. Ano: 2003 URL: http://purl.umn.edu/116061 Review of Generalized Latent Variable Modeling by Skrondal and Rabe-Hesketh AgEcon Newson, Roger. This article reviews Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models by Skrondal and Rabe-Hesketh. Tipo: Journal Article Palavras-chave: GLLAMM; Generalized linear latent and mixed models; Latent variables; Research Methods/ Statistical Methods. Ano: 2005 URL: http://purl.umn.edu/117504 Generalized power calculations for generalized linear models and more AgEcon Newson, Roger. The powercal command can compute any one of the five quantities involved in power calculations from the other four. These quantities are power, significance level, detectable difference, sample number, and the standard deviation (SD) of the influence function, which is equal to the standard error multiplied by the square root of the sample number. powercal can take arbitrary expressions (involving constants, scalars, or variables) as input and calculate the output as a new variable. The user can therefore plot input variables against output variables, and this often communicates the tradeoffs involved better than a point calculation as output by the sampsi command. General formulas are given for calculating the SD of the influence function when the... Tipo: Journal Article Palavras-chave: Powercal; Power; Alpha; Significance level; Detectable difference; Detectable ratio; Sample number; Standard deviation; Influence function; Sample design; Generalized linear model; Proportion; Arithmetic mean; Algebraic mean; Geometric mean; Odds; Research Methods/ Statistical Methods. Ano: 2004 URL: http://purl.umn.edu/116258 Confidence intervals and p-values for delivery to the end user AgEcon Newson, Roger. Statisticians make their living producing confidence intervals and pvalues. However, those in the Stata log are not ready for delivery to the end user, who usually wants to see statistical output either as a plot or as a table. This article describes a suite of programs used to convert Stata results to one or other of these forms. The eclplot package creates plots of estimates with confidence intervals, and the listtex package outputs a Stata dataset in the form of table rows that can be inserted into a plain TeX, LaTeX, HTML, or word processor table. To create a Stata dataset that can be output in these ways, we can use the parmest, dsconcat, and lincomest packages to create datasets with one observation per estimated parameter; the sencode, tostring,... Tipo: Journal Article Palavras-chave: Confidence interval; P-value; Plot; Table; Estimation results; TeX; LaTeX; HTML; Word processor; Presentation; Eclplot; Listtex; Parmest; Dsconcat; Lincomest; Sencode; Tostring; Ingap; Reshape; Descsave; Factext; Research Methods/ Statistical Methods. Ano: 2003 URL: http://purl.umn.edu/116091 Registros recuperados: 11 Primeira ... 1 ... Última

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