Data reliability is a concept used to explain the consistency or uniformity of a measure (Tracy, 2008). For instance, in a research with five respondents and each is given a test, the results should be the same no matter the number of times the test is repeated. Data validity refers to the extent to which a research accurately assesses or reflects the specific claim that the researcher is trying to measure (Tracy, 2008). In other words, reliability ensures the accuracy of a procedure or measuring instrument, whereas validity ensures the success of the research at measuring or determining what the investigator intend to measure.
Because a number of services offered by nurses are reliant on the feedback of the respondents, validity and reliability of data collection as well as the instruments used is of most significance. Nurses or the researcher need to recognize that the data collection tool selected gathers the required information. If a study cannot be depended on as reliable, then data or statistical information may not be considered or relied on in forming conclusions.
The reason for data validation is to discover and then verify data values which may not represent the issue under investigation. Procedures for effective data validation must always be handled independently from the processes of initial information collection. This is because, data collected for any study are only significant to the investigator as well as other users if accurate and valid (Carmines & Zeller, 2011). Therefore, it is important to any investigator that any data collected give accurate and valid answers to research questions (Tracy, 2008).
In summary, the significance of a test obtaining reasonable degree of validity and reliability can never be overemphasized through any means. According to Tracy (2008), there can be reliable test which is not valid, although there cannot be a valid test which is not reliable. Data reliability offers a maximum limit to validity. Data reliability and validity determines the relevance of a research to the investigator (Carmines & Zeller, 2011). Data accuracy must therefore be guaranteed to make the study significant to the researcher. Moreover, validity and reliability of the data collection tool is significant because it assists future decisions and actions.
References
Carmines, E. & Zeller, R. (2011). Reliability and validity assessment. New bury Park: Sage Publications.
Tracy, G. (2008). Dr Tracy Gilberts’ guide on Reliability and Validity. Retrieved November 15th, 2013, from http://www.essex.ac.uk/psychology/psychology/PTR/RESTRICTED/ps114R/ps114W19.pdf
