the model has been estimated over some, but not all, of the available data, then the model using the estimated parameters can be used to predict the held-back data. If, for example, the out-of-sample mean squared error, also known as the mean squared prediction error, is substantially higher than the in-sample mean square error, this is a sign of deficiency in the model. A development in medical statistics is the use of out-of-sample cross validation techniques in meta-analysis. It forms the basis of the validation statistic, Vn, which is used to test the statistical validity of meta-analysis summary estimates. Essentially it measures a type of normalized prediction error and its distribution is a linear combination of χ2 variables of degree 1. See also All models are wrong Prediction interval Resampling (statistics) Statistical conclusion validity Statistical model specification Statistical model validation Validity (statistics) Coefficient of determination Lack-of-fit sum of squares Reduced chi-squared References Further reading ; republished in 1997 by University of Michigan Press External links How can I tell if a model fits my data? (NIST) NIST/SEMATECH e-Handbook of Statistical Methods Model Diagnostics (Eberly College of Science) Validity (statistics)