7-Step Guide to Work On Structural Equation Modeling

Do you want to measure the relationship between the research variables? Do you want to see how they relate to each other? If yes, then using the structural equation modelling method is the way to go. It is a multivariate statistical method used to analyse the structural relationships between the research variables. Many students are unaware of this important structural relationship measurement method and hence fail to establish the correct relationship between the variables. Keeping this in mind, today’s guide is all about structural equation modelling techniques and the steps involved in working on them. So, let’s get started with today’s discussion by defining this technique first.

What Is Structural Equation Modelling (SEM)?

Structural equation modelling is a powerful multivariate statistical analysis technique used to evaluate the multivariate causal relationships between the variables. This technique is a combination of factor analysis and multivariate regression analysis. It measures the relationship between latent constructs and measured variables. Do you know about these two constructs? A brief description of both is as follows:

Measured Variable. A measured variable, or MV, is the variable that is measured directly using research methods specific to the problem. For example, the weight is measured using the weight balance.

Latent Constructs. The second variable is called the latent construct. It is defined as a variable which is not measured directly. This variable is rather inferred from other variables using a mathematical model.

7-Step Guide To Work On SEM

Structural equation modelling is becoming a popular statistical technique to estimate and evaluate the causal relationships between variables. Many disciplines are using this method to study the relationships between the variables. To work on this method better, you should have a know-how of the steps involved in it. Hence, a brief description of its 7 steps is as follows:

1. Define individual varaibles

As this method is all about finding the relationship between variables, the first step involves defining those variables. Individually define all the variables theoretically and establish the hypothetical relationship between them. To define the variables in the best possible manner, you should consider conducting a pretest to evaluate each item. Most of the time, a confirmatory test is conducted in this context. However, if you are unable to conduct this test, you must buy assignment online from experts to get this test conducted by experts.

2. Developing the measurement model

The second step in performing structural equation modelling involves the development of the measurement model. The measurement model is also called a path analysis. The path analysis is the relationship between the variables shown by an arrow. You must be cautious when developing the measurement model. The arrow of the measurement model is usually drawn from the measured variable to the latent variables or constructs.

3. Design and plan the study

After the development of the model comes the study planning and design. In this step, the researcher must specify the model. This planning and specification allow the researcher to minimise the problems that he may encounter during the performance of the structural equation modelling technique. Normally, two methods are used to minimise the problems in the method. One is the order condition, and the other is the rank condition.

4. Assess the validity of the measurement model

To effectively know the relationships between the variables, the measurement model must be a valid one. An invalid and unreliable model does not bring you anything. The method which is used to measure this validity is called CFA. CFA stands for confirmatory factor analysis. In CFA, as a researcher, you compare the theoretical measurement against the reality model and check whether the model is valid or not.

5. Specifying the structural model

In this step, you draw the structural paths between the measured variable and the latent constructs. It is important to know that when you are doing this, no arrow can enter the measured variable. All the arrows must originate from the measured variable and enter into the latent construct or the variable which is going to be measured. This arrow structure shows the cause-and-effect relationship. However, if you are unable to make this kind of structural model, do not forget the experts of assignment writing services.

6. Examine the model validity

In the last step of structural equation modelling, you, as a researcher, measure the validity of the relationships between the variables. To check the validity of this model, you use a test named chi-square and see its value. If the value of the chi-square test is insignificant, then know that your structural equation model is a good fit. You have found the right relationship between the measured variables and latent variables.

Conclusion

Conclusively, structural equation modelling allows researchers to test multivariate models in a single study. As it is a combination of both factor analysis and multivariate regression analysis, this statistical method gives an accurate estimation of the relationships between the variables. The 6-step guide given above can help you a lot in carrying out this difficult test. So, read all the steps carefully.