About
The Journal of Quantitative Research Methods (JQRM) is an open-access, peer-reviewed journal dedicated to advancing the theory and application of quantitative methods in the social and behavioral sciences. Recognizing the rapid evolution of data science and computational techniques, JQRM serves as a central outlet for methodological innovation, rigorous evaluation, and practical guidance. The journal is committed to open science principles, encouraging transparency through preregistration, open data, and open code. Aims JQRM aims to promote the development, dissemination, and rigorous evaluation of quantitative research methods. The journal encourages original contributions that advance methodology, from novel statistical models to innovative data collection strategies. A core aim is to bridge the gap between methodological theory and empirical practice, providing researchers with tools to address complex research questions. JQRM also seeks to foster reproducibility and replicability by encouraging authors to share data, code, and materials. Furthermore, the journal aims to facilitate interdisciplinary collaboration by welcoming contributions from diverse fields and methodological traditions. Scope The scope of JQRM encompasses all areas of quantitative methodology relevant to the social and behavioral sciences. The journal particularly welcomes contributions that address emerging challenges in data collection, measurement, and analysis. Specific topics of interest include but are not limited to: • Survey design, sampling, and nonresponse adjustment • Experimental and quasi-experimental design, including field and natural experiments • Causal inference methods: instrumental variables, difference-in-differences, regression discontinuity • Statistical modeling: multilevel/hierarchical models, structural equation modeling, mixture models • Bayesian methods and machine learning for social science applications • Measurement theory, item response theory, and construct validation • Longitudinal data analysis, panel data, and time series methods • Meta-analysis, research synthesis, and evidence accumulation • Missing data mechanisms and modern imputation techniques • Power analysis, optimal design, and sensitivity analysis Article Types • Original Research Articles: Full-length papers that introduce novel quantitative methods or provide substantial extensions to existing techniques, supported by thorough empirical applications, simulations, or theoretical justification. • Technical Notes: Concise manuscripts focusing on specific computational algorithms, software implementations, or data visualization techniques that facilitate the application of quantitative methods. • Review Articles: Comprehensive surveys and critical evaluations of methodological developments in a subfield, including systematic comparisons of alternative approaches and recommendations for best practices. • Replication Studies: Papers that replicate previous findings using different data, alternative methods, or extended samples, with an emphasis on methodological insights and generalizability. • Tutorials and Teaching Resources: Step-by-step guides and educational materials that enable researchers to implement advanced quantitative methods using leading software packages, often including annotated code and data. Audience JQRM is designed for a broad audience comprising quantitative methodologists, applied researchers in the social and behavioral sciences, graduate students and postdoctoral researchers seeking to strengthen their methodological skills, survey methodologists, data scientists, and policy analysts who rely on quantitative evidence. The journal also serves statisticians and computational scientists interested in applications to social science problems. By publishing accessible yet rigorous content, JQRM aims to facilitate the adoption of best practices across disciplines and career stages.