V
Published online by Cambridge University Press: 23 December 2009
Summary
Vague prior: A term used for the prior distribution in Bayesian methods in the situation when there is complete ignorance about the value of a parameter. [American Journal of Epidemiology, 2005, 162, 694–703.]
Validity: The extent to which a measuring instrument is measuring what was intended, or the degree to which the inference drawn from a study is warranted.
Validity checks: A part of data editing in which a check is made that only allowable values or codes are given for the answers to questions asked of subjects. A negative height, for example, would clearly not be an allowable value.
Variable: Some characteristic that differs from subject to subject or from time to time.
Variance: A measure of the spread or dispersion of a random variable around its mean. Generally assessed by the sum of squared deviations of a set of sample observations from their arithmetic mean divided by n―1, where n is the sample size. This provides an unbiased estimator of the population value. [Altman, D. G., 1991, Practical Statistics for Medical Research, Chapman and Hall/CRC, Boca Raton, FL.]
Variance components: A term generally used for the variances of random effects in statistical models, for example mixed-effects models. Particularly important in quantitative genetics where phenotypic variation is often partitioned into genetic variation, environmental variation, and the interaction of genetic and environmental variation. [Searle, S.R., Casella, G. and McCulloch, C. E., 1992, Variance Components, J. Wiley & Sons, New York.]
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- Information
- Medical Statistics from A to ZA Guide for Clinicians and Medical Students, pp. 241 - 244Publisher: Cambridge University PressPrint publication year: 2006