Unequal probability sampling in fixed area plots of stem volume with and without prior inclusion probabilities

Steen Magnussen

Journal of Applied Statistics, 2000, vol. 27, issue 8, pages 975-990

Abstract: The impact of guessing auxiliary population attributes, as opposed to relying on actual values from a prior survey, was quantified for three unequal probability sampling methods of tree stem volume (biomass). Reasonable prior guesses (no-list sampling) yielded, in five populations and 35 combinations of population size and sample size, results at par with sampling with known auxiliary predictors (list sampling). Realized sample sizes were slightly inflated in no-list sampling with probability proportional to predictions ( PPP ). Mean absolute differences from true totals and root mean square errors in no-list-sampling schemes were only slightly above those achieved with list sampling. Stratified sampling generally outperformed PPP and systematic sampling, yet the latter is recommended due to consistency between observed and expected mean square errors and overall robustness against a systematic bias in no-list settings.

Date: 2000
References: View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/02664760050173300 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:taf:japsta:v:27:y:2000:i:8:p:975-990

Ordering information: This journal article can be ordered from
http://www.tandf.co.uk/journals/subscription.asp

Access Statistics for this article

Journal of Applied Statistics is edited by Professor Gopal K. Kanji

More articles in Journal of Applied Statistics from Taylor and Francis Journals
Series data maintained by Michael McNulty ().