scholarly journals Modeling continuous self-report measures of perceived emotion using generalized additive mixed models.

2014 ◽  
Vol 19 (1) ◽  
pp. 155-174 ◽  
Author(s):  
Gary J. McKeown ◽  
Ian Sneddon
Keyword(s):  
Mixed Models ◽  
Self Report ◽  
Generalized Additive Mixed Models ◽  
Additive Mixed Models ◽  
Perceived Emotion

scholarly journals THE COGNITIVE PROCESSING OF DERIVED NOUNS WITH AMBIGUOUS SUFFIXES: BEHAVIORAL AND EYEMOVEMENT STUDY

2019 ◽  
Vol 12 (1) ◽  
pp. 85-104
Author(s):  
Isidora Gatarić
Keyword(s):  
Experimental Study ◽  
Cognitive Processing ◽  
Mixed Models ◽  
Lexical Processing ◽  
Sentence Context ◽  
Distributed Morphology ◽  
Decision Task ◽  
Generalized Additive Mixed Models ◽  
Additive Mixed Models ◽  
Movement Study

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.

scholarly journals Do Daily Fluctuations in Psychological and App-Related Variables Predict Engagement With an Alcohol Reduction App? A Series of N-Of-1 Studies (Preprint)

2019 ◽  
Author(s):  
Olga Perski ◽  
Felix Naughton ◽  
Claire Garnett ◽  
Ann Blandford ◽  
Emma Beard ◽  
...  
Keyword(s):  
Mixed Models ◽  
Perceived Usefulness ◽  
Group Level ◽  
Individual Level ◽  
Generalized Additive Mixed Models ◽  
Additive Mixed Models ◽  
The Individual ◽  
Rate Ratios ◽  
Ecological Momentary ◽  
Alcohol Reduction

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.

scholarly journals Generalized Additive Mixed-Models for Pharmacology Using Integrated Discrete Multiple Organ Co-Culture

PLoS ONE ◽  
2016 ◽  
Vol 11 (4) ◽  
pp. e0152985 ◽  
Author(s):  
Thomas Ingersoll ◽  
Stephanie Cole ◽  
Janna Madren-Whalley ◽  
Lamont Booker ◽  
Russell Dorsey ◽  
...  
Keyword(s):  
Mixed Models ◽  
Multiple Organ ◽  
Generalized Additive Mixed Models ◽  
Additive Mixed Models
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