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Validity Vs Reliability – An Overview of the Differences, Types & Examples

Home / Blog / Validity Vs Reliability – An Overview Of The Differences, Types & Examples

Validity Vs Reliability
 krishna   Published On Apr 12, 2021 | Updated on Aug 8, 2022  Assignment  0

In the world of research, reliability and validity are used to analyze the quality of research. Before we dig deeper to learn about validity vs reliability, let's first understand what each of these terms means individually.

When it comes to the reliability vs validity definition, reliability is about the consistency of a measure, whereas validity refers to a measure's accuracy. Validity and reliability play a vital role in research work, especially for creating research design, planning research methods and writing quantitative research results.

Validity Vs Reliability with Examples: Exploring the Types of Reliability

In reliability, the accuracy is determined by stable and consistent results.

 Types of Reliability

  • Test-retest reliability

It is a measure obtained by conducting a test twice to evaluate the results' stability over time.

Example: Let's say a group of students took a class test twice. The results for individual students and the correlation of results indicate stability.

  • Interrater reliability

The measure determines if different people obtain the same result after conducting the measure. Such reliability is beneficial when observers don't necessarily interpret the answers, and raters may disagree on how a response demonstrates skills and knowledge.

Example:  Interrater reliability is used when judgments are relatively subjective.

  • Internal consistency reliability

It evaluates if one gets the same results from different test items constructed to produce the same results. There are two subparts of internal consistency reliability:

  • Average inter-item correlation – It is measured by taking all the similar test items and determining the correlation for each pair, and finally calculating the average of all the correlations.
  • Split-half reliability – Let’s say you’ve drafted a questionnaire for evaluating your skill sets. Once you split the questionnaire into two halves, the aim is to develop a strong correlation. If the results vary, it indicates low internal consistency.

Reliability Vs Validity with Examples: Assessing the Types of Validity

While validity and reliability are closely related, the main argument concerning validity vs reliability is that reliability shows how consistent a particular measure is without considering its accuracy.

Validity refers to how well a method measures what it is supposed to measure. Reliability may be necessary but not sufficient. A test should be valid to be reliable.

For example, let’s say you are using a thermometer to measure your body temperature, but the scale is off by some degrees. It may consistently give you the same result after measuring your body temperature. Still, it may is not valid as it adds to your actual temperature and therefore is not valid.

Types of Validity

  • Construct Validity 

It ensures the exact measure of the existing knowledge and theory. The panel of experts can evaluate the items and determine which one to measure.

Example: An examination can be used to evaluate a student's knowledge relevant to various concepts. The strong correlation between each concept score would indicate high construct validity.

  • Criterion-Related Validity 

It measures the results that correlate test results of other similar concepts.

Example: Before the elections, various surveys analyze the political opinions of different voters in a region. If the poll results accurately predict the future of the election results, it shows that the survey reports have high criterion validity.

  • Formative Validity

It is applied to assess how a measure provides details to enhance the program of study.

Example: When designing a study program in history for students, the aim is to assess their knowledge of the subject. If the measure provides information on a student's lack of expertise in a specific area, it improves a student's course requirements.

  • Content Validity

It ensures to cover the measurement of all concepts under study. 

Example: When drafting an assessment for film studies, you cannot only focus on the acting part. You must include the other areas such as sound, lighting, and other operational functions. Such assessment will help you measure the overall content area.

Understanding Validity Vs Reliability

Ensuring Validity & Reliability In Research

Validity is considered when you choose the way to collect data. For ensuring validity in research:

  • Choose the suitable measurement methods to get the exact measure that you want to know. For instance, to gather information about personality, you can create a questionnaire based on the previous study reports.
  • Select appropriate sampling methods to pick out subjects.  To provide generalized results, define the people involved, such as their age range, location, profession, etc. Gather sufficient candidates for representing a larger population.

Reliability is considered during the data collection process. For ensuring reliability in research:

  • Careful and consistent application of data collection methods to ensure the same process for every measurement. For example, while conducting interviews, make sure to define the questions or responses, so it's the same each time.
  • Set consistent circumstances of your research to reduce the impact of other external factors on the results.

Validity Vs Reliability: Writing It In A Thesis

If you are wondering where to write about validity and reliability in a research paper, well, there are various sections.

  • Literature Review: What is other researchers' role in formulating and improving methods to make them more reliable?
  • Methodology: Your research plan for ensuring reliability and validity.
  • Results: Calculate reliability and validity and state the values alongside results.
  • Discussion: Discuss how reliable and valid your results were and if they were consistent and reflected good values. In case it didn't, discuss why not.
  • Conclusion: If you are findings show issues with reliability and validity, mention them in this section.

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