PMID- 20534159
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20110714
LR  - 20211020
IS  - 1742-7622 (Electronic)
IS  - 1742-7622 (Linking)
VI  - 7
IP  - 1
DP  - 2010 Jun 9
TI  - Bayes-LQAS: classifying the prevalence of global acute malnutrition.
PG  - 3
LID - 10.1186/1742-7622-7-3 [doi]
AB  - Lot Quality Assurance Sampling (LQAS) applications in health have generally 
      relied on frequentist interpretations for statistical validity. Yet health 
      professionals often seek statements about the probability distribution of unknown 
      parameters to answer questions of interest. The frequentist paradigm does not 
      pretend to yield such information, although a Bayesian formulation might. This is 
      the source of an error made in a recent paper published in this journal. Many 
      applications lend themselves to a Bayesian treatment, and would benefit from such 
      considerations in their design. We discuss Bayes-LQAS (B-LQAS), which allows for 
      incorporation of prior information into the LQAS classification procedure, and 
      thus shows how to correct the aforementioned error. Further, we pay special 
      attention to the formulation of Bayes Operating Characteristic Curves and the use 
      of prior information to improve survey designs. As a motivating example, we 
      discuss the classification of Global Acute Malnutrition prevalence and draw 
      parallels between the Bayes and classical classifications schemes. We also 
      illustrate the impact of informative and non-informative priors on the survey 
      design. Results indicate that using a Bayesian approach allows the incorporation 
      of expert information and/or historical data and is thus potentially a valuable 
      tool for making accurate and precise classifications.
FAU - Olives, Casey
AU  - Olives C
AD  - Harvard School of Public Health, Boston, MA, 02115, USA. 
      colives@hsph.harvard.edu.
FAU - Pagano, Marcello
AU  - Pagano M
LA  - eng
PT  - Journal Article
DEP - 20100609
PL  - England
TA  - Emerg Themes Epidemiol
JT  - Emerging themes in epidemiology
JID - 101232986
PMC - PMC2903572
EDAT- 2010/06/11 06:00
MHDA- 2010/06/11 06:01
PMCR- 2010/06/09
CRDT- 2010/06/11 06:00
PHST- 2009/07/20 00:00 [received]
PHST- 2010/06/09 00:00 [accepted]
PHST- 2010/06/11 06:00 [entrez]
PHST- 2010/06/11 06:00 [pubmed]
PHST- 2010/06/11 06:01 [medline]
PHST- 2010/06/09 00:00 [pmc-release]
AID - 1742-7622-7-3 [pii]
AID - 10.1186/1742-7622-7-3 [doi]
PST - epublish
SO  - Emerg Themes Epidemiol. 2010 Jun 9;7(1):3. doi: 10.1186/1742-7622-7-3.