1, when it is necessary to study the relationship between multiple variables: SEM can consider the relationship between multiple predicted variables and result variables at the same time, and study the complex relationship between variables.
2. When your data contains missing values: SEM can handle the data with missing values, without deleting rows or columns with missing values like some statistical analysis methods.
3, when your data does not conform to the normal distribution: SEM does not require high normality of data, and can handle data that does not conform to the normal distribution.
Knowledge expansion
"Model" is an abstract and simplified representation of things or phenomena in the real world. In science, engineering, art and other fields, models are widely used to help people understand the nature and laws of things, make predictions and plans, and realize design and manufacturing.
There are many models, which can be divided into different types according to different classification standards. For example, according to the materials and manufacturing methods used, models can be divided into physical models, virtual models, mathematical models and so on. According to the object and purpose of simulation, the model can be divided into conceptual model, physical model and mathematical model.
Conceptual model is a common model type, which is a conceptual representation of things or phenomena in the real world. Conceptual model is usually used to describe complex things or phenomena, abstracting things or phenomena in the real world into a series of concepts and relationships, helping people to better understand their essence and laws.
For example, in biology, the conceptual model of cells can abstract complex cell structures and functions into a series of simple concepts and relationships, which can help people better understand the essence of cells and the laws of life processes.
Physical model is a more specific model type, which simulates the physical properties of things or phenomena in the real world. Physical models are usually used to simulate the appearance, structure and function of things and help people better understand their physical properties and laws.
For example, in architecture, the physical model of buildings can help people better understand the appearance, structure and function of buildings, so as to design and plan.
Mathematical model is an abstract model type, which is a mathematical representation of things or phenomena in the real world. Mathematical models are usually used to describe the development laws and trends of things and help people make predictions and plans. For example, in economics, the mathematical model of economic growth can help people predict the trend of economic growth and the possibility of future development.
In a word, the model is an abstract and simplified representation of things or phenomena in the real world, which is used to help people understand the nature and laws of things, make predictions and plans, and realize design and manufacturing. Different models have different characteristics and uses, so it is necessary to choose the appropriate model according to the specific situation.