Bayes Factors for Comparison of Two-Way ANOVA Models

Vijayaragunathan, R.; Srinivasan, M. R.

doi:10.2991/jsta.d.201230.001

Cited by 7 publications

(4 citation statements)

References 11 publications

(20 reference statements)

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“…Hence, the resulting BFs for interaction effects presented in this article reflect a comparison between a model that includes the interaction term and one that includes terms for main effects only (for a more comprehensive explanation of computing Bayes Factors for the comparison of two-way ANOVA models, see Wagenmakers et al. 2018a ; Vijayaragunathan and Srinivasan 2020 ).…”

Section: Methodsmentioning

confidence: 99%

Attentional modulation of beta-power aligns with the timing of behaviorally relevant rhythmic sounds

et al. 2022

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It is largely unknown how attention adapts to the timing of acoustic stimuli. To address this, we investigated how hemispheric lateralization of alpha (7–13 Hz) and beta (14–24 Hz) oscillations, reflecting voluntary allocation of auditory spatial attention, is influenced by tempo and predictability of sounds. We recorded electroencephalography while healthy adults listened to rhythmic sound streams with different tempos that were presented dichotically to separate ears, thus permitting manipulation of spatial–temporal attention. Participants responded to stimulus-onset-asynchrony (SOA) deviants (−90 ms) for given tones in the attended rhythm. Rhythm predictability was controlled via the probability of SOA deviants per block. First, the results revealed hemispheric lateralization of beta-power according to attention direction, reflected as ipsilateral enhancement and contralateral suppression, which was amplified in high- relative to low-predictability conditions. Second, fluctuations in the time-resolved beta-lateralization aligned more strongly with the attended than the unattended tempo. Finally, a trend-level association was found between the degree of beta-lateralization and improved ability to distinguish between SOA-deviants in the attended versus unattended ear. Differently from previous studies, we presented continuous rhythms in which task-relevant and irrelevant stimuli had different tempo, thereby demonstrating that temporal alignment of beta-lateralization with attended sounds reflects top-down attention to sound timing.

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Section: Methodsmentioning

confidence: 99%

Attentional modulation of beta-power aligns with the timing of behaviorally relevant rhythmic sounds

et al. 2022

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“…For the Bayesian inference of σ 2 in a normal model, we used the Gamma prior on the inverse of variance. The shape and scale of inverse-gamma distribution are used as prior density ( Vijayaragunathan & Srinivasan, 2021 ). If the value of g -prior is 1, the prior is given the same weight as sample and the prior is 1/ p th important of the sample for a p value of g -prior ( Wetzels et al, 2012 ).…”

Section: Methodsmentioning

confidence: 99%

COVID-19 influence on commuters' attitude towards riding public buses for essential trips

Amin

Adah

2022

Cities

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“…The estimating Bayes factor for repeated-measures analysis of variance design 1 was addressed by Faulkenberry (2020). These priors are considered in the comparison of hierarchical twoway ANOVA models 10 by Vijayaragunathan and Srinivasan (2020). Bayes factors were conceptually extensively discussed by Maruyama (2009), Wetzels et al (2012), and Wang and Sun (2014).…”

Section: Priors and Bayes Factorsmentioning

confidence: 99%

Comparisons of Bayes factors for 𝟐𝟒 full, fractional, and reduced factorial designs

Vijayaragunathan¹,

Srinivasan²

2022

Int. j. adv. appl. sci.

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The effect of factors in full and fractional factorial designs is being studied ubiquitously in all fields of science and engineering. At times, researchers would want to gather additional information than the fractional factorial design provided, there is no restriction to conducting more experimental runs. In this study, we propose a reduced fractional factorial design consisting of all significant factors. This paper illustrates the effectiveness of factors through real data application and simulation by comparing the full factorial, reduced factorial, and fractional factorial designs. The actual weightage of the main/interaction effects in these three designs was found by identifying and quantifying the Bayes factors through the simulation datasets. It is observed that the reduced factorial design produces better results when there are no constraints to select or add factors to the model.

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Bayes Factors for Comparison of Two-Way ANOVA Models

Cited by 7 publications

References 11 publications

Attentional modulation of beta-power aligns with the timing of behaviorally relevant rhythmic sounds

Attentional modulation of beta-power aligns with the timing of behaviorally relevant rhythmic sounds

COVID-19 influence on commuters' attitude towards riding public buses for essential trips

Comparisons of Bayes factors for 𝟐𝟒 full, fractional, and reduced factorial designs

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