Studies on the hypothesis testing of the slope parameter in the simple linear regression model with one-fold nested error structure

Lee-Ing Tong, Paul L. Cornelius

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Six hypothesis testing procedures for the slope, β1, in the simple linear regression model with one-fold nested-error structure were investigated and compared with respect to Type I error rate and power of test in a Monte Carlo simulation study. Test criteria considered were one exact F-test, four pseudo F-tests and an approximate χ2-test obtained from each of the following four estimators of β1: the ordinary least squares (OLS), maximum likelihood (ML), estimated generalized least squares (GLS) using analysis of variance estimates of variance components, and the “covariance” estimator (COV) which uses only within-first-stage unit information. In the OLS case the F-statistic used a linear combination of mean squares as the denominator with degrees of freedom (d.f.) determined by Satterth waite's approximation. In the GLS and ML cases the F-statistic was the F-statistic obtained by fitting the model using the method of Fuller and Battese (1973). Two different allocations of the denominator d.f. were used for the GLS F-statistic, namely, the GLS1 method using total error d.f. and the GLS2 method using subsampling error d.f. In the case of COV, the test was the same as the F-test obtained for the slope of regression in a one-way analysis of covariance. In the ML case an approximate χ2test was also considered. GLS1 and ML F-tests behaved very similarly and were usually liberal. They became quite liberal if the number of first-stage sampling units a < 5 and the second-stage units per first-stage unit n = 2. The ML F-test became excessively liberal as the first-stage variance component σ12 decreased. GLS2 appeared to be the best choice in many situations, but in a few cases it was also liberal. Such cases tend to occur when a large proportion of the variation in the regressor variable is among first-stage unit variation and the d.f among first-stage sampling units is small relative to the d.f. within first-stage units. The ML χ2 test was quite liberal in all cases. The OLS test was frequently conservative. Its conservative nature was more pronounced at α (the intended significance level of the test) =.05 or.10 than at α =. 01. Conservativeness of the OLS test tends to diminish as a increases, but tends to worsen as the number n of second-stage units per first-stage unit increases with a held constant.

Original languageEnglish
Pages (from-to)2023-2043
Number of pages21
JournalCommunications in Statistics - Theory and Methods
Volume20
Issue number7
DOIs
StatePublished - 1 Jan 1991

Keywords

  • Monte Carlo simulation
  • analysis of covariance
  • analysis of variance
  • generalized least squares
  • hierarchical classification
  • hypothesis testing
  • maximum likelihood
  • mixed models
  • power of test
  • simple linear regression
  • twostage samples

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