Types of validation

Types of validation
See also
Learning map Reliability Qualitative data Descriptive model Training objective Wardley map Parametric analysis Property assessment Functions of research

There are various types of validation':

• process validation (prospective, retrospective, revalidation)
• equipment validation (certification, measurement, quality)
• analytical method validation (mean error of results)
• computer system validation (security, reliability)
• validation of data entered in IT system
• validation of medical procedures
• validation of prediction models
• etc.

Validation is one of two major way for achieving. It means how good it reflects reality. Validation includes face validity in which specialist estimate structure of the model, establishment and result confirmation or internal conformity . It check precision of coding. Cross validity parallel effect with different models which resolving the same problems. External validity is paralleling model effect to real results on world. Predictive validity is paralleling model effect with observed incident. External validity and predictive validity are the most powerful type of validation(D.M. Eddy and others 2012, p. 733).

Validation “subjecting it to tests, such as comparing model results with events observed in reality”(D.M. Eddy and others 2012, p. 734).

Validation could be useful for definition the effects applicability. It can be useful by decision makers. Is one good way for recipients establish how well model does it(D.M. Eddy and others 2012, p. 736).

Criteria

It is not practicable to write criteria which model need to have. Model could contains a lot of standards of validity for alternative applications. Validation need to fit to special applications, not to fit to the one model. There could be fragility about some issue of the model regardless of the quantity of validations are done(D.M. Eddy and others 2012, p. 736).

Validation process

Validation relate step of theory and data support the results of test for which validation was be used. The permanent action of validation provides basis interpretation of test results. Validation is used for right interpretation and it helps take an advantage of results and use it to improve the studied behavior. There should not be any negative consequence after proceed the results. Validation should use evidence, result of interpretation of evidence. Test effect needs to be supported by correct validation process. It s need to use knowledge but except that the most important is thinking process and connection skills with our knowledge. It is useful for whole process which need to fulfill state standards. Capacity to resolve problems is equally important for validation process(M. Kovalenko 2018, p. 65).

Development process

One of two part development process is validation. “Model validation is defined as the ‘substantiation that a model within its domain of applicability possesses a satisfactory range of accuracy consistent with the intended application of the model’”. Validity need to be concentrate of the specific model purpose(R.G. Sargent 2013, p.12).

Data validity

Model validation often does not include data validity. It is hard to do. It is costly to make accurate data. Problems with data are time consuming. These problems are very often cause of model fail(R.G. Sargent 2013, p. 17).

Examples of Types of validation

1. Client-Side Validation: This type of validation is used on the client-side to verify the correctness of data entered by the user before it is sent to the server. A common example of this type of validation is a form that requires a user to enter their email address. The client-side validation code will check that the email address provided is in a valid format before it is sent to the server.
2. Server-Side Validation: Server-side validation is used to verify the correctness of data entered by the user after it has been sent to the server. This type of validation is typically used to ensure that the data entered meets certain requirements, such as a minimum length or a valid format. An example of this type of validation would be ensuring that a user’s password is at least 8 characters long before it is saved in the database.
3. Data Verification: Data verification is the process of checking the accuracy and consistency of data. This type of validation is used to ensure that the data entered into a system is valid and correct. An example of this type of validation is a bank's identity verification system that requires a user to enter their name, address, and date of birth to verify their identity.
4. Business Rule Validation: Business rule validation is used to ensure that certain business rules are followed. This type of validation checks that the data entered meets certain criteria and is in compliance with the business rules. An example of this type of validation would be a system that requires a user to enter their age before they are allowed to sign up for an account.

Advantages of Types of validation

Validation is a process used to ensure that data is accurate and reliable. It is important to ensure that data is accurate before it is used in any application. There are several types of validation that can be used to ensure accuracy and reliability. The following are some of the advantages of each type of validation:

• Formal Validation: This type of validation ensures the accuracy and reliability of data across multiple systems. It is a useful tool for organizations that are responsible for managing large amounts of data.
• Automated Validation: Automated validation is an efficient way to validate data quickly and accurately. This type of validation can be used in situations where manual validation is not feasible.
• Manual Validation: Manual validation is a slower and more labor-intensive process, but it can be used to ensure accuracy and reliability in cases where automated validation is not feasible.
• Statistical Validation: Statistical validation is a method of validating data using statistical models. This type of validation is useful for ensuring that the data is representative of the population it is being used to represent.
• Semantic Validation: Semantic validation is a process that ensures that data is valid and relevant to the context in which it is being used. This type of validation can help ensure that data is being used appropriately.
• Visual Validation: Visual validation is a process that uses visual cues to help ensure accuracy and reliability of data. This type of validation can be used to quickly identify errors and mistakes in data.

Limitations of Types of validation

Validation is the process of ensuring that data, processes, and systems meet certain criteria in order to be accepted or approved. Validation is often used to check for accuracy, completeness, consistency, or conformity to a standard. There are various types of validation, however, each type of validation comes with its own set of limitations. These limitations include:

• Accuracy Validation: Accuracy validation can only be as accurate as the data that is used. If the data is incomplete, outdated, or inaccurate, then the accuracy of the validation process is compromised.
• Compliance Validation: Compliance validation can only be as effective as the compliance standards that are set. If the standards are not clear or are too lax, then compliance validation is not likely to be effective.
• Compliance Testing: Compliance testing can be time consuming, as it requires testing multiple scenarios and conditions. It can also be difficult to accurately simulate real-world scenarios and conditions.
• Security Validation: Security validation requires highly precise and specific criteria to be met in order to ensure the security of the system or process. It is also difficult to ensure that all potential threats have been identified and mitigated.
• Quality Validation: Quality validation can be difficult to measure, as quality can be subjective and vary from person to person. It can also be hard to determine what quality criteria should be considered when validating a system or process.

Other approaches related to Types of validation

Validation is a process of evaluating the correctness of data and ensuring that the data is accurate and complete. There are several types of validation, including:

• Data Validation, which involves verifying that data is accurate, complete, and within acceptable limits.
• User Interface Validation, which involves validating user input in a user interface before the data is processed.
• Business Rules Validation, which involves verifying that data meets specific business rules or criteria.
• Database Validation, which involves verifying the accuracy and completeness of data in the database.
• Security Validation, which involves verifying that user access and privileges to data are secure.

In conclusion, there are several types of validation, including Data Validation, User Interface Validation, Business Rules Validation, Database Validation, and Security Validation. Each type of validation is important to ensure that data is accurate and secure.

References

• Eddy, D. M., Hollingworth, W., Caro, J. and others (2012). Model Transparency and Validation: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force–7. Medical Decision Making (pp. 733-734, 736).
• Klügl, F. (2008, March). A validation methodology for agent-based simulations. In Proceedings of the 2008 ACM symposium on Applied computing (pp. 39-43). ACM.
• Kovalenko, M. (2018). The Validation Process in the IELTS Reading Component:Reading Requirements for Preparing International Students. Journal of Language & Education Volume 4, Issue 1 (pp. 65).
• Sargent R.G. (2013). Verification and validation of simulation models. Journal of Simulation (2013) 7,12–24 (pp.12,17).

Author: Jolanta Guz