Reliability vs Validity: What is the Difference?

There are two concepts that assist in evaluating the quality of the research – Reliability, and validity. These concepts specify how well a method, practice, or test processes something. Reliability implies the consistency of a measure, whereas validity reflects the correctness of a measure. It is essential to contemplate reliability and validity while building a research design, planning the processes and methods, and writing a research paper with the outcomes, particularly in quantitative research. Though reliability and validity are related closely and can be used interchangeably the meaning of both terms are completely different. A measurement can be reliable but it is not necessary that it will be valid also. But if a measure is valid, it is generally reliable as well.

How Reliability and Validity Can be Evaluated 

It is possible to assess reliability by comparing diverse forms of the same measurement. It is difficult to determine the validity of the measure but it can be evaluated by drawing a comparison between the outcomes with other relevant information or theory. The methods which are adopted for examining the validity, as well as reliability, can be classified into various types.

• The methods for estimating reliability through various statistical approaches are as follows –
• Test-retest

  It assesses the consistency of measurement across time and it can be done by determining whether the same results are derived when the measure is repeated. For example – a group of individuals fill a questionnaire that has been created to measure the traits of the participants. If the questionnaire is repetitive for a span of days, or weeks, or months apart and then if it provides the same results; it indicates the high test-retest reliability.

• Internal consistency

  It evaluates the uniformity of the measurement itself. It can be assessed by checking if similar results are derived from other parts of the test as well which is created to measure the same thing. For example, a questionnaire is designed to measure self-esteem, and if the results are divided into two halves, there must exist a robust correlation between both results. If the two results vary too much, then it reflects low internal consistency.

• Interrater

  It determines the consistency of measurement through observers by checking if the same results can be derived when different individuals conduct the same measurement. For example, – Five examiners submit significantly varying results for a particular student assignment as per the requirement of the grades checklist. It shows that the grades checklist has little inter-rater reliability. It is such as the measures are excessively subjective.

• The validity can be measured on the basis of three types of evidence. For assessing the validity of a cause-and-effect relationship, it is vital to consider internal and external validity. Internal validity is referred to for the design of the experiment, and external validity is referred to the generalizability of the outcomes.

The methods for assessing validity through the judgment of an expert or various statistical methods are as follows –

• Construct – It evaluates the adherence of measurement to prevailing theory and understanding of the concept which is being measured.
• Content – It assists in evaluating the level up to, which the measure covers every aspect of the concept, which is being measured.
• Criterion – It provides assistance in measuring the extent up to which the outcomes of a measure will correspond with other measures of the same concept.

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Comparison Between Reliability and Validity

• On the basis of the definitions and above discussion, a comparison can be drawn between reliability and validity. The differences between validity and reliability are as follows –

Ways to Ensure Reliability and Validity in Research

Validity and reliability depend on building a robust research design, selecting proper approaches and samples, and executing the research prudently and consistently.

• Ensuring Reliability

  Reliability must be considered all the time during the process of data collection. Ensure that the results which are derived by using specific tools are accurate and steady. For ensuring reliability pay attention to the following

• Apply Methods Consistently

  The methods must be planned carefully to ensure that similar steps are conducted in the same way for every measure. It is essential specifically when there are several researchers.

• Standardize the Circumstances of Research

  When the data is being gathered, ensure to maintain the situation consistently as much as possible in order to lessen the impact of the external elements which might cause deviations in the outcomes.

• Ensuring Validity

  It is important that the outcomes indicate the deviations as precisely as possible and it can be ensured by using the ratings or grading to measure the level of dissimilarities. It is vital that the validity must be considered in the early stages of the study, as soon as it is decided how the information will be gathered. For ensuring validity –

(i) Select the appropriate method of measurement – It is necessary to choose the methods, processes, measurement tools, and techniques of superior quality, These should be researched rigorously and wisely on the basis of current knowledge.

(ii) Proper sampling methods – Use correct sampling methods, and ensure that the selected subjects are sufficient and they represent the population.