Stepwise estimation of accommodation in multivariate anthropometric models using percentiles and an average correlation value

We estimated accommodation on multiple variables using a stepwise combination of pairs of data (percentile values), where each combined pair became an input for the succeeding step. The method is based on calculation of the covariance of intersecting sets using an average correlation value. Two different set-based definitions of accommodation are discussed, intersection, where all values are concurrently less than or equal to their respective percentile values, and union, where the sum of all measurements is less than or equal to the sum of the percentile values. Accommodation was estimated for 280 different combinations of anthropometric data formed by adding 2 to 15 variables and for 40 different combinations of 2, 5, 10 and 15 variables where one variable was subtracted from the others, a total of 320 different models. The estimates were compared with observed values; the average differences for both types of accommodation ranged between 2.2 and −6.5 per cent.