Results 271 to 280 of about 28,805 (302)

Modified Wald statistics for generalized linear models

Allgemeines Statistisches Archiv, 2004
Wald statistics in generalized linear models are asymptotically Χ2 distributed. The asymptotic chi–squared law of the corresponding quadratic form shows disadvantages with respect to the approximation of the finite–sample distribution. It is shown by means of a comprehensive simulation study that improvements can be achieved by applying simple finite ...
Andreas Oelerich, Thorsten Poddig
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A Simulation Study on a Wald Statistic and Cochran's Q Statistic for Stratified Samples

Biometrics, 1977
A Wald statistic is offered to test equality of proportions in matched samples when the probability of "success" of an observation in a given sample is constant within the stratum but possibly different between strata. Cochran's Q statistic might be used to test this hypothesis since it has been used to test equality of proportions in matched samples ...
Grant W. Somes, V. P. Bhapkar
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ON THE ASYMPTOTIC NULL-DISTRIBUTION OF THE WALD STATISTIC AT SINGULAR PARAMETER POINTS

Statistics & Risk Modeling, 1999
Summary: We consider the large sample Wald test for a nonlinear null hypothesis on a multidimensional parameter in a statistical model. The Wald statistic is known to be asymptotically chi-square distributed under the null hypothesis, provided that the Jacobian of the restriction function describing the null hypothesis has full rank. However, there may
Gaffke, Norbert, Steyer, Rolf, von Davier, Alina A.   +2 more
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A Reminder of the Fallibility of the Wald Statistic: Likelihood Explanation

The American Statistician, 2000
Abstract The Wald statistic is one of the most commonly used tools in applied statistics, so it is sobering to read Fears, Benichou, and Gail's recent reminder of its fallibility. What makes their example particularly relevant is the fact that the problem is manifest in a simple normal random effects model on a balanced dataset for a seemingly harmless
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On the application of the Wald statistic to order estimation of ARMA models

IEEE Transactions on Automatic Control, 1991
Summary: Consistent criteria for order estimation of autoregressive-moving-average (ARMA) processes based on the Wald statistic are presented. The new criteria require only the estimation of the model parameters at the largest order, unlike alternative methods in the literature that require the estimation of the model parameters at all possible orders.
Burshtein, David, Weinstein, Ehud
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The Wald Statistic in Proportional Hazards Hypothesis Testing

Biometrical Journal, 1989
AbstractIn survivorship modelling using the proportional hazards model of Cox (1972, Journal of the Royal Statistical Society, Series B, 34, 187–220), it is often desired to test a subset of the vector of unknown regression parameters β in the expression for the hazard rate at timet.
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Introduction to Wald (1949) Statistical Decision Functions

1992
Abraham Wald was born on October 31, 1902 in Cluj, one of the main cities of Transylvania, which at the time belonged to Hungary. The official language was Hungarian, but the population was mixed, containing substantial numbers of Romanian, German, and Jewish inhabitants, as well as Hungarians.
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Higher Order Approximations for Wald Statistics in Cointegrating Regressions [PDF]

, 1998
Asymptotic expansions are developed for Wald test statistics in cointegrating regression models. These expansions provide an opportunity to reduce size distortion in testing by suitable bandwidth selection, and automated rules for doing so are calculated. Band spectral regression methods and tests are also considered. In such cases, it is shown how the
Zhijie Xiao, Peter C.B. Phillips
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Revisiting the Wald Test in Small Case-Control Studies With a Skewed Covariate

American Journal of Epidemiology, 2022
William C L Stewart
exaly  

Introduction to Wald (1945) Sequential Tests of Statistical Hypotheses

1992
Probability theory came of age with the advent of Kolmogorov’s axiomatics in 1933 and the subsequent developments in limit theorems and stochastic processes. Statistical inference came of age with the advent of the Neyman-Pearson theory in 1933 and the subsequent formalization of hypothesis testing, estimation, and decision theory. In the present paper,
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