Testing fixed and random effects in linear mixed models

Marco Barnabani ()
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Marco Barnabani: Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", Università di Firenze, https://www.disia.unifi.it

No 2020_09, Econometrics Working Papers Archive from Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti"

Abstract: In linear mixed models the selection of fixed and random effects using a testing hypothesis approach brings up several problems. In this paper, we consider the so called boundary problem and the confounding impact of effects from one set of coefficient in the other set. These problems are addressed by defining two test statistics based on ordinary least squares obtained by dividing two quadratic forms, one that contains the effect and another that does not. As a result, the test statistics are sufficiently general, easy to compute, with known finite sample properties. The test on randomness has a known exact distribution under the null and alternative hypothesis, the test on fixed effect is approximated by a noncentral F -distribution. Because of its importance in the selection variable approach, the goodness-of-approximation is examined in-depth in final simulations.

Keywords: Selection procedure; Hypothesis testing; Linear Mixed Models; Generalized F -distribution (search for similar items in EconPapers)
JEL-codes: C12 C52 C63 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2020-12
New Economics Papers: this item is included in nep-ecm
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