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      How relative frequency and prosodic structure affect the acoustic duration of English derivatives

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      Laboratory Phonology
      Open Library of the Humanities

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          Abstract

          Morphological segmentability, i.e., the degree to which complex words can be decomposed into their morphological constituents, has been considered an important factor in research on morphological processing and is expected to affect acoustic duration (e.g., Hay, 2001, 2003). One way of operationalizing segmentability is through the relative frequency of a complex word to its base word. However, relative frequency has failed to affect duration for different affix categories in many previous studies. One potential reason is the fact that complex words vary in their prosodic structure, depending on the prosodic integration of the affix (Plag & Ben Hedia, 2018).In a large corpus study with three different corpora and eight affixes each, we investigate how prosodic word structure and relative frequency influence duration, and how these two factors interact. We find that prosodic structure does not significantly interact with relative frequency. Second, we show that relative frequency effects on duration do not emerge consistently across a large number of affixes. Third, not only does prosodic word structure not explain the absence of relative frequency effects, it also often cannot account for durational differences as such. We discuss these findings in light of phonological theory and speech production models.

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          Fitting Linear Mixed-Effects Models Usinglme4

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            Bayesian Model Selection in Social Research

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              A practical solution to the pervasive problems of p values.

              In the field of psychology, the practice of p value null-hypothesis testing is as widespread as ever. Despite this popularity, or perhaps because of it, most psychologists are not aware of the statistical peculiarities of the p value procedure. In particular, p values are based on data that were never observed, and these hypothetical data are themselves influenced by subjective intentions. Moreover, p values do not quantify statistical evidence. This article reviews these p value problems and illustrates each problem with concrete examples. The three problems are familiar to statisticians but may be new to psychologists. A practical solution to these p value problems is to adopt a model selection perspective and use the Bayesian information criterion (BIC) for statistical inference (Raftery, 1995). The BIC provides an approximation to a Bayesian hypothesis test, does not require the specification of priors, and can be easily calculated from SPSS output.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Laboratory Phonology
                Open Library of the Humanities
                1868-6354
                February 9 2022
                March 30 2022
                : 13
                : 1
                Affiliations
                [1 ]Heinrich Heine University Düsseldorf
                Article
                10.16995/labphon.6445
                9a971cf5-f2cb-424e-90a8-ad2f7f9798e9
                © 2022

                https://creativecommons.org/licenses/by/4.0

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