Research Topic

Statistical Guidelines: New Developments in Statistical Methods and Psychometric Tools

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About this Research Topic

Quantitative methods and psychometrics have revolutionized research in psychology, neuroscience and in the broader field of cognitive science. The need for objective measures to catch, analyse and make sense of human behaviour is a must for psychology as a science. Moreover, even though the null hypothesis ...

Quantitative methods and psychometrics have revolutionized research in psychology, neuroscience and in the broader field of cognitive science. The need for objective measures to catch, analyse and make sense of human behaviour is a must for psychology as a science. Moreover, even though the null hypothesis significance testing (NHST) is the most common method of statistical inference used in psychological science, NHST showed theoretical and practical flaws. The advent of innovative and advanced quantitative and statistical methods in psychometrics helped us to better understand the complexity of the brain and human behaviour overcoming classic methods of psychometrics and allowing a new vision of data.

The present Research Topic has three key aims:
1) providing innovative and advanced quantitative and statistical methods in the field of psychology (e.g. clinical, experimental, social), neuroscience (e.g. clinical, cognitive and affective) and more in general in psychological science as a whole;
2) disseminating new psychometric tools, such as hardware (e.g. technological, psychophysiological, neurophysiological instruments), software or algorithms; and,
3) evaluating the efficacy and advantages of new methods compared to classic psychometric tools and methods.

As part of this collection we welcome systematic reviews, meta-analyses, methods papers, original research papers, perspectives, commentaries, opinion articles, clinical trials and case studies. In particular, we highly appreciate papers that show the advantages of: innovative statistical topics (e.g. Bayesian statistics, item response theory, regression, statistical significance), machine learning and algorithms, computational methods in psychology and neuroscience, new technologies in psychometrics (e.g. virtual reality, mobile, sensors, brain computer interface) and software, for diagnosis, assessment, treatment efficacy evaluation and Big Data analysis.

Potential topics include but are not limited to the following:
- Bayesian inference
- Bayesian statistics
- item response theory
- regression
- statistical significance testing
- statistical power
- Hypothesis testing
- reproducibility
- p-value
- supervised machine learning
- unsupervised machine learning
- neural networks
- network analysis
- A.I.
- computational neuroscience
- neurophysiology
- psychophysiology
- software
- virtual reality
- mobile
- BCI
- sensors
- affective neuroscience
- cognitive neuroscience


Keywords: Statistics, Computational Psychometrics, Neurophysiology, Psychophysiology, Behavioural, Cognitive, Affective, Machine learning, Classification, Regression, Bayes, Assessment, Big Data, New Technologies, Software, Hardware, Data Mining, Brain Computer Interface, A.I.


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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