scholarly journals Analyzing phonetic data with generalized additive mixed models

Author(s):  
Yu-Ying Chuang ◽  
Janice Fon ◽  
R. H. Baayen

This chapter provides a user's guide to analysing phonetic data with the Generalized Additive Model (GAM). We show how GAMs can be used to capture the different kinds of nonlinear effects and patterns that are ubiquitous in phonetic data. To illustrate how GAMs work, we present analyses of three datasets of Taiwan Mandarin, addressing nonlinearities in time series of experimental response times, in F0 contours, and in the geographic distribution of sociophonetic variation. By building models incrementally, we clarify the kinds of problem that arise at various stages of analysis, and show how these can be addressed within the GAM framework. In our analyses, we also show how variation between individual speakers can be accounted for.

2020 ◽  
Author(s):  
Yu-Ying Chuang ◽  
Ching-Chu Sun ◽  
Janice Fon ◽  
R. H. Baayen

This study investigates the geographical distribution of pronunciation variation of voiceless dental and retroflex sibilants in Taiwan Mandarin. Previous studies indicated that the merging of the two sibilants is geographically dependent (Line, 1983; Chuang, 2009). However, the geographical effects in these studies are not easy to interpret due to the limited number of speakers and regions. For the current study, we recruited 331 native speakers of Taiwan Mandarin from 120 regions in Taiwan. In a picture-naming task, 30 dental/retroflex-initial words were elicited from each speaker. The data were analysed with Generalized Additive Mixed models (Wood, 2004). The analysis revealed a robust effect of geographical location, with merging being less common in metropolitan cities as compared to the surrounding areas.


2019 ◽  
Vol 12 (1) ◽  
pp. 85-104
Author(s):  
Isidora Gatarić

The primary aim of this research has been to investigate whether the suffix ambiguity affects the lexical processing of derived nouns in Serbian. Consequently, in the Experiment 1, the derived nouns were presented isolated to participants in the visual lexical decision task. Bearing in mind that the sentence context was important for the lexical processing, the Experiment 2 was designed as an eye-movement study with the sentences (with derived nouns from the Experiment 1) as stimuli. To the best of our knowledge, the similar experimental study was not performed before in the Serbian language, and therefore this study represents the first attempt to investigate this phenomenon in Serbian. An identical statistical analysis was used to analyze the data collected in both experiments, the Generalized Additive Mixed Models (GAMMs). The final results of all GAMMs analyses suggested that the suffixal ambiguity did not affect the lexical processing of derived nouns in Serbian, regardless of whether they were displayed isolated or in the sentence context. The observed results supported the a-morphous perspective in the morpho-lexical processing, as well as the distributed morphology insights from the theoretical linguistics.


Author(s):  
Olga Perski ◽  
Felix Naughton ◽  
Claire Garnett ◽  
Ann Blandford ◽  
Emma Beard ◽  
...  

BACKGROUND Previous studies have identified psychological and smartphone app–related predictors of engagement with alcohol reduction apps at a group level. However, strategies to promote engagement need to be effective at the individual level. Evidence as to whether group-level predictors of engagement are also predictive for individuals is lacking. OBJECTIVE The aim of this study was to examine whether daily fluctuations in (1) the receipt of a reminder, (2) motivation to reduce alcohol, (3) perceived usefulness of the app, (4) alcohol consumption, and (5) perceived lack of time predicted within-person variability in the frequency and amount of engagement with an alcohol reduction app<italic>.</italic> METHODS We conducted a series of observational <italic>N</italic>-of-1 studies. The predictor variables were measured twice daily for 28 days via ecological momentary assessments. The outcome variables were measured through automated recordings of the participants’ app screen views. A total of nine London-based adults who drank alcohol excessively and were willing to set a reduction goal took part. Each participant’s dataset was analyzed separately using generalized additive mixed models to derive incidence rate ratios (IRRs) for the within-person associations of the predictor and outcome variables. Debriefing interviews, analyzed using thematic analysis, were used to contextualize the findings. RESULTS Predictors of the frequency and amount of engagement differed between individuals, and for the variables 'perceived usefulness of the app' and 'perceived lack of time', the direction of associations also differed between individuals. The most consistent predictors of within-person variability in the frequency of engagement were the receipt of a daily reminder (IRR=1.80-3.88; <italic>P</italic>&lt;.05) and perceived usefulness of the app (IRR=0.82-1.42; <italic>P</italic>&lt;.05). The most consistent predictors of within-person variability in the amount of engagement were motivation to reduce alcohol (IRR=1.67-3.45; <italic>P</italic>&lt;.05) and perceived usefulness of the app (IRR=0.52-137.32; <italic>P</italic>&lt;.05). CONCLUSIONS The utility of the selected psychological and app-related variables in predicting the frequency and amount of engagement with an alcohol reduction app differed at the individual level. This highlights that key within-person associations may be masked in group-level designs and suggests that different strategies to promote engagement may be required for different individuals.


Sign in / Sign up

Export Citation Format

Share Document