Types of Reliability in Quantitative Research

In research studies, reliability refers to the consistency or stability of a measurement instrument over time and across different contexts. This concept is crucial in quantitative research as it ensures that the data collected is accurate and trustworthy. While accuracy focuses on the degree of closeness between the measured value and the true value, reliability examines whether the same results are obtained even when the same measurement process is repeated.

One common myth about reliability is that a thermometer must be accurate to be reliable. However, this is not necessarily true. A thermometer can be unreliable if it changes its readings despite no change in temperature. In contrast, a reliable thermometer will consistently provide the same reading even when the temperature remains constant.

Sociologists use various methods to assess the reliability of measurement instruments. These include:

1. Test-retest procedure: This involves administering the same questionnaire or instrument to a group of participants at two different times to see if the results are consistent.

2. Alternate forms procedure: This method involves comparing the results obtained from two different versions of the same instrument to determine if they yield similar outcomes.

3. Split-halves procedure: In this approach, the items in a questionnaire or instrument are split into two halves and each half is administered separately to assess consistency.

4. Internal consistency procedure: This method examines the degree of correlation among the items in an instrument to ensure that they measure the same construct.

Good measurement instruments should have both high reliability and high accuracy. While reliability ensures consistency, accuracy focuses on the precision of the measurements. Ideally, a reliable instrument with high accuracy will provide consistent results that are close to the true value.

In this study, we investigated the reliability of indicators used to measure the impact of Enterprise Risk Management (ERM) implementation on the performance of non-state higher education institutions in Sri Lanka. Our sample consisted of 170 senior professionals selected from a population of 707 senior persons attached to non-state institutions in Sri Lanka using stratified random sampling technique.

The results of our investigation showed that the Cronbach's alpha value for each latent variable was above the threshold of 0.70, indicating high reliability and consistency among the items used to measure the constructs. Our findings provide insight into the types of risks faced by non-state higher education institutions in Sri Lanka, including strategic, operational, financial, compliance, technological, and reputational risks.

The implementation of ERM is crucial for entities to identify, assess, and mitigate overall risks. However, many research studies have concluded that the significant positive relationship between ERM implementation and firm performance remains inconclusive due to the high cost of implementing ERM systems and the inability to justify increasing performances. Our study highlights the importance of examining the reliability of indicators used in such investigations to ensure accurate and trustworthy results.

By understanding the different types of reliability in quantitative research, researchers can ensure that their measurement instruments are reliable and consistent, providing a solid foundation for drawing conclusions about the phenomenon being studied.

Types of reliability in quantitative research