Estimating Detection Limits in Ultratrace Analysis. Part I: The Variability of Estimated Detection Limits

Abstract

The limit of detection (LOD) of a trace analytical method is often used as a gauge of the sensitivity of the method. Improvements and comparisons of similar methods usually involve comparisons of the LODs. However, the calculated LOD value is sensitive to a number of factors such as the method of calculation used, the choice of calibration standards, and the number background (blank) measurements. In this paper, the calculated LOD of a particular analytical method is viewed as an estimate of the true, unknown LOD. Factors which affect the variability of the estimate are investigated. Knowledge of the variability of the estimated LOD can help when analytical methods are being compared on the basis of LOD values. In addition, by knowing which experimental factors contribute to the uncertainty in the calculated LOD, it is possible to determine the analytical protocol which estimates the true LOD most efficiently with no loss in precision.

Keywords

Detection limits

Get full access to this article

View all access options for this article.

References

Vera

J. A.

Leong

M. B.

Omenetto

Smith

B. W.

Womack

and Winefordner

J. D

, Spectrochim. Acta 44B, 939 (1989).

Johnson

P. A.

Barber

T. E.

Smith

B. W.

and Winefordner

J. D

, Anal. Chem. 61, 861 (1989).

IUPAC Analytical Chemistry Division, Spectrochim. Acta 33B, 242 (1978).

Kaiser

, Two Papers on the Limit of Detection of a Complete Analytical Procedure (Hafner, New York, 1969).

Currie

L. A.

, Anal. Chem. 40, 586 (1968).

Long

G. L.

and Winefordner

J. D

, Anal. Chem. 55, 712A (1983).

The Analytical Methods Committee, Analyst 112, 199 (1987).

Draper

N. R.

and Smith

, Applied Regression Analysis (Wiley, New York, 1981), 2nd ed.

Oppenheimer

Capizzi

T. P.

Weppelman

R. M.

and Mehta

, Anal. Chem. 55, 638 (1983).

10.

Hubaux

and Vos

, Anal. Chem. 42, 849 (1970).

11.

Mitchell

D. G.

and Garden

J. S

, Talanta 29, 921 (1982).

12.

Clayton

C. A.

Hines

J. W.

and Elkins

P. D

, Anal. Chem. 59, 2506 (1987).

13.

Boumans

P. W. J. M.

, Spectrochim. Acta 33B, 625 (1978).

14.

Hald

, Statistical Theory with Engineering Applications (Wiley, New York, 1952).

15.

Mandel

, The Statistical Analysis of Experimental Data (Wiley, New York, 1964).

16.

Walpole

R. E.

and Myers

R. H

, Probability and Statistics for Engineers and Scientists (MacMillan, New York, 1989), 4th ed., Chap. 7.

17.

Smith

B. W.

Farnsworth

P. B.

Cavalli

and Omenetto

, Spectrochim. Acta 45B, 1369 (1990); Smith

B. W.

, private communication.

18.

Voigtman

and Winefordner

J. D

, Prog. Analyt. Atom. Spectrosc. 9, 7 (1986).

19.

Knuth

D.E.

, The Art of Computer Programming (Addison-Wesley, Reading, Massachusetts, 1969), Vol. 2, p. 104.

20.

Wei

G.-T.

Dougherty

J. P.

Preli

F. R.

Jr. , and Michel

R. G.

J. Anal. At. Spectrosc. 5, 249 (1990).

21.

Mark

and Workman

, Spectroscopy 4, 56 (1989).

22.

Berkson

, J. Amer. Statistical Assn. 45, 164 (1950).

23.

Neter

Wasserman

and Kutner

M. H

, Applied Linear Statistical Models (Richard D. Irwin Inc., Homewood Illinois, 1985), 2nd ed., p. 166.