Quantitative methods and psychometrics have come a long way in recent decades. The arrival of innovative and advanced statistical and quantitative methods has been surpassing the classic methods in psychometrics, allowing a new vision of the data. On the other hand, although the null hypothesis significance test (NHST) is the most common method of statistical inference used in psychological science, Bayesian statistics is making its way out of the classical inference methods.
The aim of this Research Topic is to disseminate innovations in measurement, research methodology, and quantitative analysis in Psychology and other social sciences, as well as to evaluate the efficacy and advantages of the new methods in comparison with classical tools and methods. Theoretical, quantitative, empirical, and methodological original articles are requested. We aim to collect articles that show the advantages of innovative statistical topics (Bayesian statistics, Bayesian structural equation modeling, latent class analysis, statistical significance, etc.), reviews of methodological topics of current interest, simulation studies evaluating the behavior of indices, power, sample size, etc., meta-analyses on existing practices, articles that explain new and innovative applications of procedures applied to the resolution of psychological problems, and reviews of statistical software. This Research Topic welcomes also submissions that show the relevance to the psychology of procedures developed in other fields. Empirical or theoretical articles can include applications using novel methodologies such as Multilevel Structural Equation Modeling or Multilevel Latent Class Analysis.
Therefore, in this Research Topic, we wish to collect papers about the most recent innovations in measurement, research methodology, and quantitative analysis in psychology and other social sciences, and the following types of articles are welcomed:
• Original studies focused on new and advanced methodologies;
• Papers that show the advantages or benefits of innovative statistical topics;
• Simulation studies evaluating the behavior of indices, power, sample size, etc.;
• Meta-analysis of existing practices;
• Opinion articles;
• Reviews of methodological topics of current interest;
• Reviews of statistical software or hardware.
Quantitative methods and psychometrics have come a long way in recent decades. The arrival of innovative and advanced statistical and quantitative methods has been surpassing the classic methods in psychometrics, allowing a new vision of the data. On the other hand, although the null hypothesis significance test (NHST) is the most common method of statistical inference used in psychological science, Bayesian statistics is making its way out of the classical inference methods.
The aim of this Research Topic is to disseminate innovations in measurement, research methodology, and quantitative analysis in Psychology and other social sciences, as well as to evaluate the efficacy and advantages of the new methods in comparison with classical tools and methods. Theoretical, quantitative, empirical, and methodological original articles are requested. We aim to collect articles that show the advantages of innovative statistical topics (Bayesian statistics, Bayesian structural equation modeling, latent class analysis, statistical significance, etc.), reviews of methodological topics of current interest, simulation studies evaluating the behavior of indices, power, sample size, etc., meta-analyses on existing practices, articles that explain new and innovative applications of procedures applied to the resolution of psychological problems, and reviews of statistical software. This Research Topic welcomes also submissions that show the relevance to the psychology of procedures developed in other fields. Empirical or theoretical articles can include applications using novel methodologies such as Multilevel Structural Equation Modeling or Multilevel Latent Class Analysis.
Therefore, in this Research Topic, we wish to collect papers about the most recent innovations in measurement, research methodology, and quantitative analysis in psychology and other social sciences, and the following types of articles are welcomed:
• Original studies focused on new and advanced methodologies;
• Papers that show the advantages or benefits of innovative statistical topics;
• Simulation studies evaluating the behavior of indices, power, sample size, etc.;
• Meta-analysis of existing practices;
• Opinion articles;
• Reviews of methodological topics of current interest;
• Reviews of statistical software or hardware.
