HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (8) Citing Articles via Google Scholar Google Scholar Articles by Virtanen, A. Articles by Uusipaikka, E. Search for Related Content PubMed PubMed Citation Articles by Virtanen, A. Articles by Uusipaikka, E. Related Collections Laboratory Management Pediatric Clinical Chemistry Hematology

Regression-based reference limits: determination of sufficient sample size

¹ Central Laboratory, University Central Hospital of Turku/Mircit (Medical Informatics Research Centre in Turku), FIN-20521 Turku, Finland.
Departments of
² Clinical Chemistry and
³ Statistics, University of Turku, FIN-20500 Turku, Finland.
^a Author for correspondence. Fax 358-2-2613920; e-mail arja.virtanen{at}utu.fi.

Regression analysis is the method of choice for the production of covariate-dependent reference limits. There are currently no recommendations on what sample size should be used when regression-based reference limits and confidence intervals are calculated. In this study we used Monte Carlo simulation to study a reference sample group of 374 age-dependent hemoglobin values. From this sample, 5000 random subsamples, with replacement, were constructed with 10–220 observations per sample. Regression analysis was used to estimate age-dependent 95% reference intervals for hemoglobin concentrations and erythrocyte counts. The maximum difference between mean values of the root mean square error and original values for hemoglobin was 0.05 g/L when the sample size was 60. The parameter estimators and width of reference intervals changed negligibly from the values calculated from the original sample regardless of what sample size was used. SDs and CVs for these factors changed rapidly up to a sample size of 30; after that changes were smaller. The largest and smallest absolute differences in root mean square error and width of reference interval between sample values and values calculated from the original sample were also evaluated. As expected, differences were largest in small sample sizes, and as sample size increased differences decreased. To obtain appropriate reference limits and confidence intervals, we propose the following scheme: (a) check whether the assumptions of regression analysis can be fulfilled with/without transformation of data; (b) check that the value of v, which describes how the covariate value is situated in relation to both the mean value and the spread of the covariate values, does not exceed 0.1 at minimum and maximum covariate positions; and (c) if steps 1 and 2 can be accepted, the reference limits with confidence intervals can be produced by regression analysis, and the minimum acceptable sample size will be ~70.

The following articles in journals at HighWire Press have cited this article:

				M Thompson, A Harnden, R Perera, R Mayon-White, L Smith, D McLeod, and D Mant Deriving temperature and age appropriate heart rate centiles for children with acute infections Arch. Dis. Child., May 1, 2009; 94(5): 361 - 365. [Abstract] [Full Text] [PDF]

				D. Zurakowski, J. Di Canzio, and J. A. Majzoub Pediatric Reference Intervals for Serum Thyroxine, Triiodothyronine, Thyrotropin, and Free Thyroxine Clin. Chem., July 1, 1999; 45(7): 1087 - 1091. [Full Text] [PDF]

				E. M Wright and P. Royston Calculating reference intervals for laboratory measurements Statistical Methods in Medical Research, April 1, 1999; 8(2): 93 - 112. [Abstract] [PDF]