✦ LIBER ✦

A note on hypothesis testing in LAV multiple regression: A small sample comparison

✍ Scribed by Terry E. Dielman; Elizabeth L. Rose

Publisher: Elsevier Science
Year: 1996
Tongue: English
Weight: 450 KB
Volume: 21
Category: Article
ISSN: 0167-9473
DOI: 10.1016/0167-9473(95)00022-4

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

A note on the generalization of some res

A note on the generalization of some results in hypothesis sampling theory

✍ Mary Ann Fisher 📂 Article 📅 1971 🏛 Elsevier Science 🌐 English ⚖ 191 KB

A note on in-sample and out-of-sample te

A note on in-sample and out-of-sample tests for Granger causality

✍ Shiu-Sheng Chen 📂 Article 📅 2005 🏛 John Wiley and Sons 🌐 English ⚖ 90 KB

This paper studies in-sample and out-of-sample tests for Granger causality using Monte Carlo simulation. The results show that the out-of-sample tests may be more powerful than the in-sample tests when discrete structural breaks appear in time series data. Further, an empirical example investigating

A Note on Maximum Likelihood Ratio Test

A Note on Maximum Likelihood Ratio Test of No Outliers in Regression Models

✍ Prof. S. R. Paul 📂 Article 📅 1986 🏛 John Wiley and Sons 🌐 English ⚖ 180 KB 👁 2 views

A derivation of the maximum likelihood ratio test for testing no outliere in regreeeion models h given ueing the method of WETEXEILL (1981, pp. 106-107) for estimating the regreeeion parsmetere. This method h eseentially eimilar to the one outlined in B a s m and Lmwm (1978, p. 283), although by our

A note on a comparison of confidence int

A note on a comparison of confidence interval techniques in truncated life tests

✍ W. E. Coleman; T. Jayachandran; D. R. Barr 📂 Article 📅 1971 🏛 John Wiley and Sons 🌐 English ⚖ 190 KB

A note on the computation of robust, bou

A note on the computation of robust, bounded influence estimates and test statistics in regression

✍ Douglas P. Wiens 📂 Article 📅 1992 🏛 Elsevier Science 🌐 English ⚖ 848 KB

A comparison of one-sided methods to ide

A comparison of one-sided methods to identify significant individual outcomes in a multiple outcome setting: stepwise tests or global tests with closed testing

✍ James F. Troendle; Julie M. Legler 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 141 KB 👁 1 views

We compare two approaches to the identification of individual significant outcomes when a comparison of two groups involves multiple outcome variables. The approaches are all designed to control the familywise error rate (FWE) with any subset of the null hypotheses being true (in the strong sense).