Reliability indicates how constantly a method estimates anything. For example, you will achieve the corresponding result with the corresponding sample on which you use the same method under the corresponding condition. Otherwise, the measuring method may not be reliable.

Different Types of Reliability

There’re four types of reliability, and you can estimate them by examining various results sets obtained using the corresponding method:

Test-retest Reliability

This is one of the types of reliability that determines the uniformity of outcomes when a particular test is performed repeatedly on the corresponding sample at some other period. Thus, use such reliability to measure something that is expected to be uniform in a sample.

A colour blindness test for pilot candidates must have great test-retest, as it is a characteristic that remains the same over time.

This type of reliability is important because results can be influenced many times. For instance, respondents may experience various feelings, or external situations may influence their capability to respond the same way.

This test also assesses the resistance of a method against factors after a certain period. The lesser the discrepancy between two results sets, the more the test-retest reliability.

To measure this type of reliability, you should schedule the corresponding test with the same people at distinct times. Then, you should compute the relation between these two outcomes.

Test-retest Reliability: Example

You prepare a questionnaire to determine a particular participant group’s intelligence quotient (a property unlikely to alter substantially over time) and give the test to them two months before. Unfortunately, you observed the outcomes vary largely, so the reliability is low.

Increasing Reliability of Test-retest

• When you design a test or questionnaire, try creating statements, questions, and tasks that will not be affected by the concentration level or mood of the participants involved.
• When you plan your data collection methods, try minimising external factors’ influence and ensure that testing of every sample is under the similar condition.
• Recall all the changes that participants may experience with time and consider them.

Interrater Reliability
This stands second in our list and is also referred to as interobserver reliability and determines the agreement level amongst a group of people determining the same item. It’s used when researchers have to assign scores, ratings, categories, or scores to one or more than one variable and are required to collect data.

A researcher’s team gather information on classroom behaviour. This is why it is important. Moreover, every researcher should conform to a categorisation method or rate various behaviour types.

This type of reliability can be measured by researchers conducting the corresponding measurement on the corresponding sample and compute the relation between a variety of results. In case every researcher gives equivalent scores, the test will have great interrater reliability.

Example of Interrater Reliability
A researchers’ team assess the progression of wound healing in a particular hospital’s patients. They use rating scales to document the healing stages with guidelines to determine different wound phases. The results obtained by researchers determining the same patients will be contrasted. There’s a sturdy relationship amongst all results sets, so such reliability is higher.

Increasing Interrater Reliability

• Describe methods and variables you will use to gauge the reliability.
• Generate objective and detailed rules for how you are planning to rate, count, or categorise the variables.
• If your study involves multiple researchers, ensure they all received the same training and information.

Parallel Forms Reliability

This type of reliability is used to determine the relationship between two similar test versions. So you can apply it if you’ve two varied question sets or tools sets prepared to determine the corresponding thing.

If you wish to utilise different test versions (for instance, avoiding respondents from repeating their answers), you must ensure that all measurements or question sets provide reliable outcomes.

In scholarly assessments, formulating various test versions is usually important so that learners don’t know the questions before time. It means that the same learners take two various reading comprehension tests, they shall get equivalent outcomes in both the tests.

It can be measured by producing a large question set to determine the corresponding thing and then distribute them arbitrarily into two various sets of questions.

The corresponding respondents attend both sets afterwards and compute the relation amongst the result sets. Again, a high correlation shows a high level of reliability.

Example of Parallel Forms Reliability
Various questions are prepared to compute the monetary risk amongst the respondents. These respondents and questions are then arbitrarily put into two various sets and two groups, respectively. One group answers test A, and the second group answers test B. The two results are then compared and are nearly identical, denoting a higher parallel form of reliability.

Increasing Parallel Forms Reliability

• Assure that every question or test item is as per the corresponding system as well as created to develop the corresponding thing.

Internal Consistency
It determines the relationship amongst various things mentioned in the test, meant to assess the corresponding contrive.

Such reliability can be computed without giving the test or including other researchers again, so it is a feasible way to assess reliability if you have only one set of data.

When you create a question set or ratings consolidated into a complete score, you must ensure that every item reflects the corresponding thing. If answers to various items differ from each other, the test then may not be reliable.

To compute the customer satisfaction rate with a store, you can formulate a questionnaire comprising statements that participants will conform or not conform with. This type of reliability dictates the reliability of the listed statements to determine customer satisfaction.

You can measure internal consistency using the following two basic methods:

• Average Inter-item Relation: You need to compute the relation amongst the outcomes of every possible pair of an item and the average for different measures you have prepared to determine the same construct
• Split-half Reliability: You divide the measures into two sets randomly. After you test the participants, you compute the relation between each set.

Example of Internal Consistency
The respondents are given the statements to assess positive and negative outlooks. They shall mark their agreement from 1-5 with every statement. If the test you have given is internally consistent, a positive respondent will give higher ratings to positive indicators and comparatively lesser marks to negative indicators. The relation is computed between the “negative” statements responses, but the relation is fragile, indicating less internal consistency reliability.

Increasing Internal Consistency

• Devise measures or questions carefully: those likely to show the same idea should be as per the same system and formulated vigilantly.

In Conclusion
You must consider reliability while outlining research design, gathering as well as analysing your information, and documenting the research you have conducted. You must choose one out of all the types of reliability as per the research type you wish to conduct and your research methodology.

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