Structural equation modeling (SEM) is a powerful statistical technique that is used to analyze and understand complex relationships between variables. There are two main types of SEM: covariance-based SEM (CB-SEM) and partial least squares SEM (PLS-SEM). [...]

Qualitative data triangulation refers to the use of multiple sources or methods to collect and analyze data in a research study. This approach aims to increase the validity and reliability of the findings by providing multiple perspectives and reducing the potential for bias. [...]

Exploratory data analysis (EDA) is a crucial step in the data analysis process, where analysts seek to understand the patterns, trends, and relationships within a dataset. It involves summarizing the data, visualizing it in various forms, and identifying any anomalies or outliers. [...]

Multiple regression and structural equation modeling (SEM) are two popular statistical methods used in social sciences, psychology, and business research to analyze the relationships between multiple variables. Both methods are widely used to examine the relationships between independent variables [...]

ANOVA, or Analysis of Variance, is a statistical technique used to determine whether there is a significant difference between the means of two or more groups. It was first introduced by statistician Ronald A. Fisher in 1925 as a way to test hypotheses about the mean of a population. [...]

The question of which comes first in psychometric testing, reliability or validity, is a debated topic in the field of psychometrics. Some argue that reliability must be established before validity, while others argue that validity must be established before reliability. [...]