Importance of data collection and subgroup analyses in research methodology

Abstract

Data collection serves as the cornerstone in the study of clinical research questions. Two types of data are commonly utilized in medicine: (1) Qualitative; and (2) Quantitative. Several methods are commonly employed to gather data, regardless of whether retrospective or prospective studies are used: (1) Interviews; (2) Observational methods; (3) Questionnaires; (4) Investigation parameters; (5) Medical records; and (6) Electronic chart reviews. Each source type has its own advantages and cons in terms of the accuracy and availability of the data to be extracted. We will focus on the important parts of the research methodology: (1) Data collection; and (2) Subgroup analyses. Errors in research can arise from various sources, including investigators, instruments, and subjects, making the validation and reliability of research tools crucial for ensuring the credibility of findings. Subgroup analyses can either be planned before or emerge after (post-hoc) treatment. The interpretation of subgroup effects should consider the interaction between treatment effect and various patient variables with caution.

Keywords: Data collection; Methodology; Research; Journal; Academic

Core Tip: A variety of methods exist to assess the normality of continuous data. Among these tests, the Shapiro–Wilk test, Kolmogorov–Smirnov test, skewness, kurtosis, histogram, box plot, P–P plot, Q–Q plot, and mean with standard deviation are commonly employed. Of these, the widely recognized Shapiro–Wilk test is suitable for small sample sizes (< 50 samples), although it can also accommodate larger sample sizes. Conversely, the Kolmogorov–Smirnov test finds utility when dealing with n ≥ 50, making it another prominent technique for evaluating data normality.