PMID- 24633656
OWN - NLM
STAT- MEDLINE
DCOM- 20150121
LR  - 20211021
IS  - 1097-0258 (Electronic)
IS  - 0277-6715 (Print)
IS  - 0277-6715 (Linking)
VI  - 33
IP  - 16
DP  - 2014 Jul 20
TI  - Extending cluster lot quality assurance sampling designs for surveillance 
      programs.
PG  - 2746-57
LID - 10.1002/sim.6145 [doi]
AB  - Lot quality assurance sampling (LQAS) has a long history of applications in 
      industrial quality control. LQAS is frequently used for rapid surveillance in 
      global health settings, with areas classified as poor or acceptable performance 
      on the basis of the binary classification of an indicator. Historically, LQAS 
      surveys have relied on simple random samples from the population; however, 
      implementing two-stage cluster designs for surveillance sampling is often more 
      cost-effective than simple random sampling. By applying survey sampling results 
      to the binary classification procedure, we develop a simple and flexible 
      nonparametric procedure to incorporate clustering effects into the LQAS sample 
      design to appropriately inflate the sample size, accommodating finite numbers of 
      clusters in the population when relevant. We use this framework to then discuss 
      principled selection of survey design parameters in longitudinal surveillance 
      programs. We apply this framework to design surveys to detect rises in 
      malnutrition prevalence in nutrition surveillance programs in Kenya and South 
      Sudan, accounting for clustering within villages. By combining historical 
      information with data from previous surveys, we design surveys to detect spikes 
      in the childhood malnutrition rate.
CI  - Copyright (c) 2014 John Wiley & Sons, Ltd.
FAU - Hund, Lauren
AU  - Hund L
AD  - Department of Family and Community Medicine, University of New Mexico, 2400 
      Tucker Avenue Northeast Albuquerque, NM 87131, U.S.A.
FAU - Pagano, Marcello
AU  - Pagano M
LA  - eng
GR  - R01 AI097015/AI/NIAID NIH HHS/United States
GR  - T32 AI007358/AI/NIAID NIH HHS/United States
GR  - T32 ES007142/ES/NIEHS NIH HHS/United States
GR  - R01AI097015/AI/NIAID NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
DEP - 20140317
PL  - England
TA  - Stat Med
JT  - Statistics in medicine
JID - 8215016
SB  - IM
MH  - Cluster Analysis
MH  - *Health Care Surveys
MH  - Humans
MH  - *Population Surveillance/methods
MH  - *Quality Assurance, Health Care/statistics & numerical data
MH  - *Sampling Studies
PMC - PMC4047169
MID - NIHMS572330
OTO - NOTNLM
OT  - LQAS
OT  - acceptance sampling
OT  - longitudinal surveillance
OT  - nutrition
OT  - survey design
EDAT- 2014/03/19 06:00
MHDA- 2015/01/22 06:00
PMCR- 2015/07/20
CRDT- 2014/03/18 06:00
PHST- 2013/03/07 00:00 [received]
PHST- 2014/02/11 00:00 [revised]
PHST- 2014/02/18 00:00 [accepted]
PHST- 2014/03/18 06:00 [entrez]
PHST- 2014/03/19 06:00 [pubmed]
PHST- 2015/01/22 06:00 [medline]
PHST- 2015/07/20 00:00 [pmc-release]
AID - 10.1002/sim.6145 [doi]
PST - ppublish
SO  - Stat Med. 2014 Jul 20;33(16):2746-57. doi: 10.1002/sim.6145. Epub 2014 Mar 17.