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      Antepenultimate stress in Spanish: In defense of syllable weight and grammatically-informed analogy

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          Abstract

          Spanish has a contrastive stress system with three major possibilities: antepenultimate, penultimate, and final stress. While penultimate and final stress are to some extent predictable, a major point of contention in the literature is whether antepenultimate stress assignment is rule-governed ( Harris 1983; Roca 1991; i.a.). By examining different analogical and grammatically-informed models and their predictive power in capturing experimental data, I show that a Maximum Entropy model ( Hayes & Wilson 2008) that includes syllable weight in its lexical representations is the best predictor of antepenultimate stress assignment. In doing so, I also dispute the claim that the trill in Spanish is a geminate tap ( Harris 1983), and provide support for its status as a singleton consonant.

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          Fitting Linear Mixed-Effects Models Using lme4

          Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. Journal of Statistical Software, 67 (1) ISSN:1548-7660
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            Simultaneous inference in general parametric models.

            Simultaneous inference is a common problem in many areas of application. If multiple null hypotheses are tested simultaneously, the probability of rejecting erroneously at least one of them increases beyond the pre-specified significance level. Simultaneous inference procedures have to be used which adjust for multiplicity and thus control the overall type I error rate. In this paper we describe simultaneous inference procedures in general parametric models, where the experimental questions are specified through a linear combination of elemental model parameters. The framework described here is quite general and extends the canonical theory of multiple comparison procedures in ANOVA models to linear regression problems, generalized linear models, linear mixed effects models, the Cox model, robust linear models, etc. Several examples using a variety of different statistical models illustrate the breadth of the results. For the analyses we use the R add-on package multcomp, which provides a convenient interface to the general approach adopted here. Copyright 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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              Absence of evidence is not evidence of absence.

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                Author and article information

                Contributors
                Journal
                2397-1835
                Glossa: a journal of general linguistics
                Ubiquity Press
                2397-1835
                19 July 2018
                2018
                : 3
                : 1
                : 80
                Affiliations
                [1 ]Yale University, 370 Temple St., New Haven, CT, US
                Author information
                http://orcid.org/0000-0002-6862-8422
                Article
                10.5334/gjgl.433
                e83ae908-16b4-4337-9501-56314cdfba20
                Copyright: © 2018 The Author(s)

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 May 2017
                : 09 May 2018
                Categories
                Research

                General linguistics,Linguistics & Semiotics
                maximum entropy models,analogical models,Spanish stress,phonotactics,syllable weight

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