Validity and Reliability

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Research process involves several steps and each step depends on the preceding steps. If step is missing or inaccurate, then the succeeding steps will fail. When developing research plan, always be aware that this principles critically affects the progress. One of critical aspects of evaluation and appraisal of reported research is to consider the quality of the research instrument. According to Parahoo (2006), in quantitative studies reliability and validity are two of the most important concept used by researcher to evaluate the quality of the study that is carried out. Reliability and validity in research refer specifically to the measurement of data as they will be used to answer the research question. In most
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Assessment of stability involves method of test-retest method reliability and using of alternate forms reliability.

3.2.1 Test – retest method
This is the classical test of stability called test-retest method. This method allows researchers to administer the same measure to a sample twice and then compare the scores (Polit & Beck, 2012). According to Wood & Rose-Kerr (2006), test-retest method is repeated measurements over time using the same instrument on the same subject to produce the same result. For example, a test is developed to measure knowledge of mathematics. The test is given to a group of students and repeated two weeks later. Their score in both tests must be similar if the test measure reliably. A reliable questionnaire will give consistent result over time. If the results are not consistent, the test is not considered reliable and will need to be revised until it does measure consistently.

Based on the above example, the result from the first testing can be correlated with the result of the second testing and resulted with high correlation. The comparison is performed objectively by computing a reliability coefficient, which is an index of the magnitude of the test’s reliability. Reliability coefficient usually ranges between 0.00 and 1.00. The higher the coefficient, the more stable the measure. Reliability coefficients above 0.80 usually are considered good as stated by Polit and Beck (2012). For unstable variables, the

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