Related Experiment Video
Updated: Aug 19, 2026

Quantifying Yeast Chronological Life Span by Outgrowth of Aged Cells
Published on: May 6, 2009
Estimation of age-specific reference intervals for skewed data
1Department of Community Medicine and Behavioral Sciences, Faculty of Medicine, Kuwait University, Kuwait. amoussa@hsc.kuniv.edu.kw
Objectives:
To compare Cole's LMS method with Wright and Royston's Exponential-Normal (EN) method for estimating reference intervals and generating smooth centile curves for the body mass index (weight in kg/height in meters squared) measurements of children aged 6 to 13 years.
Methods:
In the LMS method, the parameters L (the power needed to normalize the data), M (median) and S (coefficient of variation) are modeled as smoothed fits of maximum likelihood estimates. In the Exponential-Normal method, the three parameters mean, standard deviation and skewness are estimated separately using multiple regression techniques.
Results:
The centiles generated by the LMS and EN methods are close in most of the age groups. The 2.5th and 97.5th quantiles of the interval of the differences between the loss function scores of the LMS and EN methods calculated by bootstrap was found to include zero, indicating that the difference in loss function scores of the two methods is random and not systematic.
Conclusions:
The two methods are simple to use and generate comparable centile curves.
Related Concept Videos
Chebyshev's Theorem to Interpret Standard Deviation
Estimating Population Mean with Known Standard Deviation
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate + error bound)
The...
Confidence Interval for Estimating Population Mean
A confidence interval for the mean is a range of values that provides an estimate of the population mean. As the...
Distributions to Estimate Population Parameter
Estimating Population Standard Deviation
Estimating Population Mean with Unknown Standard Deviation
William S. Gosset (1876–1937) of the Guinness...

