Bayesian Hypothesis Testing Approach Research Articles

The relationship between sociosexual orientation, muscle performance and disgust sensitivity: a preliminary correlational study.

Sociosexual orientation (SO), muscle performance (MP), and disgust sensitivity (DS) play a crucial role in sexual life. Previous research reported a relationship between SO and muscle strength, but the association across these variables has not been fully investigated. This study aimed to evaluate the association between SO, MP, and DS. Seventy-two subjects (age: 49.7±13.7 years, 38 F) participated in the study. The SO, MP and DS were evaluated using a Sexual Attitude Scale (SAS), a revised Sociosexual Orientation Inventory (SOI-R), a body composition analysis, handgrip test (HG), a Standing Long Jump Test (SLJ), a Body Odor Disgust Scale (BODS) and Three Domains of Disgust Scale (TDDS). A strong evidence in favor of a positive association between SO and MP (r=0.52, BF<inf>10=</inf>29), inconclusive evidence for a negative correlation between SO and DS (r=-0.37, BF<inf>10</inf>=2) and moderate evidence in favor of the absence of a relationship between MP and DS (r=0.001, BF<inf>01</inf>=5) was found using a Bayesian hypothesis testing approach (Bayes Factor). Higher MP is associated with a greater tendency to have occasional relationships and multiple sexual partners, in both genders. MP-related self-esteem and perceived vulnerability may be involved in mating behaviors. We speculate that the sexual hormones might mediate the relationship among these variables. Future studies are warranted to explore this hypothesis.

The relation between sociosexual orientation, muscle performance and disgust sensitivity. A preliminary correlational study

Sociosexual orientation (SO), muscle performance (MP), and disgust sensitivity (DS) play a crucial role in sexual life. Previous research reported a relationship between SO and muscle strength, but the association across these variables has not been fully investigated. This study aimed to evaluate the association between SO, MP, and DS. Seventy-two subjects (age: 49.7±13.7 years, 38 F) participated in the study. The SO, MP and DS were evaluated using a Sexual Attitude Scale (SAS), a revised Sociosexual Orientation Inventory (SOI-R), a body composition analysis, handgrip test (HG), a Standing Long Jump Test (SLJ), a Body Odor Disgust Scale (BODS) and Three Domains of Disgust Scale (TDDS). A strong evidence in favor of a positive association between SO and MP (r=0.52, BF<inf>10=</inf>29), inconclusive evidence for a negative correlation between SO and DS (r=-0.37, BF<inf>10</inf>=2) and moderate evidence in favor of the absence of a relationship between MP and DS (r=0.001, BF<inf>01</inf>=5) was found using a Bayesian hypothesis testing approach (Bayes Factor). Higher MP is associated with a greater tendency to have occasional relationships and multiple sexual partners, in both genders. MP-related self-esteem and perceived vulnerability may be involved in mating behaviors. We speculate that the sexual hormones might mediate the relationship among these variables. Future studies are warranted to explore this hypothesis.

Age-related deficits in the congruency sequence effect are task-specific: An investigation of nine tasks.

In most attentional-control tasks, incongruent trials (i.e., trials with a conflict between two responses) are intermixed with congruent trials (i.e., trials without conflict). Typically, performance is slower and more error-prone on incongruent trials than on congruent trials. This congruency effect has been found to be smaller after incongruent trials than after congruent trials. This finding-labeled the congruency sequence effect (CSE)-has been assumed to reflect a dynamic adjustment of attentional control, which enables participants to enhance goal-relevant features and to inhibit irrelevant features. Only a few studies have investigated the impact of aging on the CSE, and their results are mixed. Compared to young adults, older adults were found to show a similar CSE, no CSE, a larger CSE, or a smaller CSE. This discrepancy in results has been interpreted as the consequence of using different tasks. To test for this, we conducted new analyses on 9 tasks-the color Stroop, number Stroop, arrow flanker, letter flanker, Simon, global-local, positive compatibility, and negative compatibility task-from our previous study (Rey-Mermet, Gade, & Oberauer, 2018). Both a null-hypothesis significance testing approach and a Bayesian hypothesis testing approach showed a similar CSE in both age groups for most tasks. Only in the Stroop tasks, the CSE was larger for older adults. These results are incompatible with the hypothesis of a general age-related deficit in attentional control. At the same time, they question the construct validity of the CSE. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

A Bayesian Approach to Measuring Evidence in L2 Research: An Empirical Investigation

AbstractNull hypothesis testing has long since been the ‘go‐to analytic approach’ in quantitative second language (L2) research (Norris, 2015, p. 97). To many, however, years of reliance on this approach has resulted in a crisis of inference across the social and behavioral sciences (e.g., Rouder et al., 2016). As an alternative to the null hypothesis testing approach, many such experts recommend the Bayesian hypothesis testing approach. Adopting an open‐science framework, the present study (a) re‐evaluates the empirical findings of 418 t‐tests from published L2 research using Bayesian hypothesis testing, and (b) compares the Bayesian results with their conventional, null hypothesis testing counterparts as observed in the original reports. The results show that the Bayesian and the null hypothesis testing approaches generally arrive at similar inferential conclusions. However, considerable differences arise in the rejections of the null hypothesis. Notably, in 64.06% of cases when p‐values fell between .01 and .05 (i.e., evidence to reject the null), the Bayesian analysis found the evidence in the primary studies to be only at an ‘anecdotal’ level (i.e., insufficient evidence to reject the null). Practical implications, field‐wide recommendations, and an introduction to free online software (https://rnorouzian.shinyapps.io/bayesian-t-tests) for Bayesian hypothesis testing are discussed.

A large scale test of the gaming-enhancement hypothesis.

A growing research literature suggests that regular electronic game play and game-based training programs may confer practically significant benefits to cognitive functioning. Most evidence supporting this idea, the gaming-enhancement hypothesis, has been collected in small-scale studies of university students and older adults. This research investigated the hypothesis in a general way with a large sample of 1,847 school-aged children. Our aim was to examine the relations between young people’s gaming experiences and an objective test of reasoning performance. Using a Bayesian hypothesis testing approach, evidence for the gaming-enhancement and null hypotheses were compared. Results provided no substantive evidence supporting the idea that having preference for or regularly playing commercially available games was positively associated with reasoning ability. Evidence ranged from equivocal to very strong in support for the null hypothesis over what was predicted. The discussion focuses on the value of Bayesian hypothesis testing for investigating electronic gaming effects, the importance of open science practices, and pre-registered designs to improve the quality of future work.

A Multi-scale Bayesian Hypothesis Testing Approach for the Analysis of Prepulse Inhibition Test

Prepulse inhibition (PPI) deficits have been seen in various neuropsychiatric disorders, such as schizophrenia, Tourette’s syndrome and Huntington’s disease. How to effectively distinct these PPI deficit subjects from normal ones is a challenging task because the PPI data measured from animal experiments are usually erroneous, incomplete, and unstable. In this paper, we introduce a novel multi-scale Bayesian hypothesis testing (MBHT) method to rectify the PPI data. Specifically, we regard any startle response signal as a deteriorated result from a hypothesis and reconstruct the complete and stable signal using a Bayesian hypothesis testing approach. The multi-scale analysis here is necessary because we cannot directly estimate the proper scale for a hypothesis even we have some statistical quantities of the whole population. By carrying out two sets of animal experiments using different medicines, we show that this MBHT method is much more robust than the conventional method. The analytic methodology proposed in this work can also be applied to similar animal experiments.

A BAYESIAN HYPOTHESIS TESTING APPROACH FOR FINDING UPPER BOUNDS FOR PROBABILITIES THAT PAIRS OF SOFTWARE COMPONENTS FAIL SIMULTANEOUSLY

Predicting the reliability of software systems based on a component-based approach is inherently difficult, in particular due to failure dependencies between software components. One possible way to assess and include dependency aspects in software reliability models is to find upper bounds for probabilities that software components fail simultaneously and then include these into the reliability models. In earlier research, it has been shown that including partial dependency information may give substantial improvements in predicting the reliability of compound software compared to assuming independence between all software components. Furthermore, it has been shown that including dependencies between pairs of data-parallel components may give predictions close to the system's true reliability. In this paper, a Bayesian hypothesis testing approach for finding upper bounds for probabilities that pairs of software components fail simultaneously is described. This approach consists of two main steps: (1) establishing prior probability distributions for probabilities that pairs of software components fail simultaneously and (2) updating these prior probability distributions by performing statistical testing. In this paper, the focus is on the first step in the Bayesian hypothesis testing approach, and two possible procedures for establishing a prior probability distribution for the probability that a pair of software components fails simultaneously are proposed.

Spectrum reuse at the border of a primary user cell

Most algorithms for secondary spectrum usage are solely based on signal detection. The frequencies where the primary signal is detected with level comparable to the noise are considered occupied. As a result vast areas in the proximity of primary cells become illegal for spectrum reuse. In this paper we propose an algorithm that enhances spatial spectrum reuse by allowing secondary users to communicate in the presence of primary signal. We study how much the spectrum utilization is increased by using the proposed algorithm. The algorithm has multiple decision stages and it is based both on signal detection and generated interference estimation. It allows to minimize the decision errors and control the generated interference to primary user receivers. The algorithm is modeled by using Bayesian hypothesis testing approach. The required prior probabilities are related to the geographical interpretation of the studied system. The constructed model allows to find the optimal decision levels through the Lagrangian optimization. The algorithm performance is evaluated as a function of the number of measured power samples. Comparison to a simple detection based scheme indicates recognizable improvement especially for a low number of samples.