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      Intonation, yes and no

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          Abstract

          English polar particles yes and no are interchangeable in response to negative sentences, that is, either one can be used to convey both positive and negative responses. We provide a critical discussion of recent research into this phenomenon ( Kramer & Rawlins 2009; Krifka 2013; Roelofsen & Farkas 2015; Holmberg 2016), which leads to three questions: Does the intonation produced on yes and no depend on whether the response is positive or negative, and can intonation affect the interpretation of bare polar particle responses? Which particles do speakers prefer to use when? Are preference patterns sensitive to the polarity of preceding sentences in the context? In a series of experiments, we demonstrate that the contradiction contour ( Liberman & Sag 1974) is an intonation that is commonly produced on positive responses to negative sentences, and that it affects hearers’ interpretations of bare particle responses. Beyond intonation, our experimental results add new evidence regarding speakers’ preferences for using yes and no in response to negative polar questions and rising declaratives. Finally, our results suggest that preference patterns are not sensitive to the polarity of context sentences.

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          Random effects structure for confirmatory hypothesis testing: Keep it maximal.

          Linear mixed-effects models (LMEMs) have become increasingly prominent in psycholinguistics and related areas. However, many researchers do not seem to appreciate how random effects structures affect the generalizability of an analysis. Here, we argue that researchers using LMEMs for confirmatory hypothesis testing should minimally adhere to the standards that have been in place for many decades. Through theoretical arguments and Monte Carlo simulation, we show that LMEMs generalize best when they include the maximal random effects structure justified by the design. The generalization performance of LMEMs including data-driven random effects structures strongly depends upon modeling criteria and sample size, yielding reasonable results on moderately-sized samples when conservative criteria are used, but with little or no power advantage over maximal models. Finally, random-intercepts-only LMEMs used on within-subjects and/or within-items data from populations where subjects and/or items vary in their sensitivity to experimental manipulations always generalize worse than separate F 1 and F 2 tests, and in many cases, even worse than F 1 alone. Maximal LMEMs should be the 'gold standard' for confirmatory hypothesis testing in psycholinguistics and beyond.
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            Categorical Data Analysis: Away from ANOVAs (transformation or not) and towards Logit Mixed Models.

            This paper identifies several serious problems with the widespread use of ANOVAs for the analysis of categorical outcome variables such as forced-choice variables, question-answer accuracy, choice in production (e.g. in syntactic priming research), et cetera. I show that even after applying the arcsine-square-root transformation to proportional data, ANOVA can yield spurious results. I discuss conceptual issues underlying these problems and alternatives provided by modern statistics. Specifically, I introduce ordinary logit models (i.e. logistic regression), which are well-suited to analyze categorical data and offer many advantages over ANOVA. Unfortunately, ordinary logit models do not include random effect modeling. To address this issue, I describe mixed logit models (Generalized Linear Mixed Models for binomially distributed outcomes, Breslow & Clayton, 1993), which combine the advantages of ordinary logit models with the ability to account for random subject and item effects in one step of analysis. Throughout the paper, I use a psycholinguistic data set to compare the different statistical methods.
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              Analyzing Linguistic Data

              R. Baayen (2008)
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                Author and article information

                Contributors
                Journal
                2397-1835
                Glossa: a journal of general linguistics
                Ubiquity Press
                2397-1835
                10 January 2018
                2018
                : 3
                : 1
                : 5
                Affiliations
                [1 ]McGill University, 1085 ave Dr. Penfield, Montréal, QC, H3A 1A7, CA
                Author information
                http://orcid.org/0000-0003-2953-106X
                Article
                10.5334/gjgl.210
                9d707c83-0148-4e91-b9a3-7b3b44366c40
                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
                : 22 July 2016
                : 09 June 2017
                Categories
                Research

                General linguistics,Linguistics & Semiotics
                contradiction contour,questions,prosody,intonation,no,yes,polar particles

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