It is the technical error in particular that we aim to minimse, but it is important to have an idea of the total error associated with a particular measurement.

error associated with the instruments you use to take a measure and the skills of the researcher in taking the measure). the body is constantly changing and providing different results) or technical error (e.g. The error can come from biological error (e.g. Of course the results aren't exactly the same, there is error associated with the measurement. give them a drink when assessing hydration status, waiting a year to measure body mass), what is the likelihood that I would get the same result? It is obviously important that repeat measures are fairly close. It's like asking: If I took the measure again, without doing anything that is likely to change the measure (e.g. Reliability refers to the reproducibility of a measure if you were to repreat the measure. If you don't measure these things yourself, you should at the very least make a case for how valid the measures that you are taking generally are from evidence presented in the literature. You quantify validity by comparing your measurements with values that are as close to the true values as possible, often referred to as a 'gold standard'. doi:10.1016/j.sapharm.2018.03.Validity refers to the agreement between the value of a measurement and its true value. Evaluation of methods used for estimating content validity. Encyclopedia of Autism Spectrum Disorders. Encyclopedia of Quality of Life and Well-Being Research. Psychological Testing in the Service of Disability Determination. doi:10.1037/a0026975Ĭommittee on Psychological Testing, Including Validity Testing, for Social Security Administration Disability Determinations Board on the Health of Select Populations Institute of Medicine. Defining and distinguishing validity: Interpretations of score meaning and justifications of test use. Standards for talking and thinking about validity.

Validity and reliability of data