Mixed methods research: Definition, types, benefits, and challenges
Independent variables are the predictors you set or measure first, and dependent variables are the outcomes recorded afterward. Define the two variables with clear units, timing, and coding;
Hauntingly easy data tricks: Tips for organizing and analyzing mixed methods data
Mixed methods research doesn’t have to be overwhelming—structured data collection and smart use of tools like NVivo, ATLAS.ti, and XLSTAT can simplify the entire process. From transcribing interviews to organizing field notes and running statistical analyses, staying disciplined and methodical is the key to turning messy data into meaningful insights.
How AI tools for academic research writing support synthesis and analysis
AI can enhance the research writing process when used with care, clarity, and intent. With integrated tools like NVivo and Citavi, researchers can streamline workflows while maintaining scholarly integrity.
Behind the breakthroughs: Using XLSTAT to understand consumer acceptance of biofortified foods
Consumer acceptance is critical for the success of biofortified foods—nutritional value alone isn’t enough. Using XLSTAT, researchers uncovered that sweetness, light texture, and smooth mouthfeel were the strongest drivers of preference for kisra made with nutrient-rich sorghum.
Exploring Partial Least Squares Structural Equation Modeling
Exploring Partial Least Squares Structural Equation Modeling (PLS-SEM) Applications in Supply Chain Research: A Bibliometric Analysis and Science Mapping Approach
Collaborative qualitative research with NVivo for teams
Collaboration is at the center of many qualitative research projects, yet for many research teams, managing workflows can sometimes feel as complex as the data itself. So how can you navigate this challenge to foster collaboration and turn your data into collective insights?
Exploring the application of PLS-SEM in business, management, and accounting research
Sustainability and social media have emerged as dominant research themes, while critical methodological concerns, including overuse and validity issues, remain insufficiently addressed.
Mastering capital project cost risk with smarter models in @RISK
Large capital projects frequently exceed budgets and timelines, and traditional contingency planning no longer keeps pace. Learn how probabilistic models can help you take control of cost risk with @RISK through an infrastructure use case.
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Estimation of Coincident Index with Dynamic Factor Models
Stock and Watson (1989) introduced a dynamic factor model that uses a single unobserved factor to capture common movements in macroeconomic variables and measure overall economic activity.