Ranked set sampling for ecological research: accounting for the total costs of sampling

Researchers aim to design environmental studies that optimize precision and allow for generalization of results, while keeping the costs of associated field and laboratory work at a reasonable level. Ranked set sampling is one method to potentially increase precision and reduce costs by using ‘rough but cheap’ quantitative or qualitative information to obtain a more representative sample before the real, more expensive sampling is done. In this report, we investigate under what conditions ranked set sampling becomes a cost-effective sampling method for ecological and environmental field studies where the ‘rough but cheap’ measurement has a cost. Ratios of measuring to ranking costs necessary for ranked set sampling to be as cost effective as simple random sampling, for a common precision, are presented for known distributions with and without ranking error. Cost ratios are also presented for a real data set consisting of visually estimated and physically measured stream habitat areas. Results provide specific guidelines for when ranked set sampling is appropriate, and cost effective, for ecological and environmental field sampling. Copyright © 1999 John Wiley & Sons, Ltd.

[1]  Ganapati P. Patil,et al.  Relative precision of ranked set sampling: A comparison with the regression estimator , 1993 .

[2]  Geoffrey C. Poole,et al.  IN‐STREAM HABITAT UNIT CLASSIFICATION: INADEQUACIES FOR MONITORING AND SOME CONSEQUENCES FOR MANAGEMENT 1 , 1997 .

[3]  A. Winsor.  Sampling techniques. , 2000, Nursing times.

[4]  P. Yu,et al.  Regression estimator in ranked set sampling. , 1997, Biometrics.

[5]  Kosuke Imai,et al.  Survey Sampling , 1998, Nov/Dec 2017.

[6]  A. E. Sarhan,et al.  Contributions to order statistics , 1964 .

[7]  Hassen A. Muttlak,et al.  Ranked Set Sampling and the Line Intercept Method: A More Efficient Procedure , 1992 .

[8]  Douglas A. Wolfe,et al.  The Effect of Imperfect Judgment Rankings on Properties of Procedures Based on the Ranked-Set Samples Analog of the Mann-Whitney-Wilcoxon Statistic , 1994 .

[9]  Richard G. Oderwald,et al.  Evaluation of Ranked Set Sampling for Estimating Shrub Phytomass in Appalachian Oak Forests , 1980 .

[10]  G. McIntyre,et al.  A method for unbiased selective sampling, using ranked sets , 1952 .

[11]  M. S. Ridout,et al.  An investigation into the use of ranked set sampling on grass and grass-clover swards , 1985 .

[12]  M. S. Ridout,et al.  Ranked set sampling with non-random selection of sets and errors in ranking , 1987 .

[13]  A. E. Sarhan,et al.  Contributions to order statistics , 1964 .

[14]  J. L. Clutter,et al.  Ranked Set Sampling Theory with Order Statistics Background , 1972 .

[15]  Kazumasa Wakimoto,et al.  On unbiased estimates of the population mean based on the sample stratified by means of ordering , 1968 .

[16]  David G. Hankin,et al.  Estimating Total Fish Abundance and Total Habitat Area in Small Streams Based on Visual Estimation Methods , 1988 .

[17]  John R. Skalski,et al.  Detection of contaminated samples using a two‐way compositing scheme , 1994 .

[18]  S. Stokes,et al.  Ranked set sampling with concomitant variables , 1977 .

[19]  Ganapati P. Patil,et al.  Designing Cost-Effective Environmental Sampling Using Concomitant Information , 1996 .

[20]  Ganapati P. Patil,et al.  UNEQUAL ALLOCATION MODELS FOR RANKED SET SAMPLING WITH SKEW DISTRIBUTIONS , 1997 .

[21]  L. K. Halls,et al.  Trial of Ranked-Set Sampling for Forage Yields , 1966 .