Julie Vallée|Marc Souris|Florence Fournet|Audrey Bochaton|Virginie Mobillion|Karine Peyronnie|Gérard Salem
Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR)
Université Paris Nanterre|Mahidol University|Asian Institute of Technology|Institut de Recherche Pour le Développement|Université Paris Nanterre|Université Paris Nanterre|Université Paris Nanterre
geographical objectives probabilistic methods difficult reconcile unique health survey probabilistic methods focus individuals provide estimates variables prevalence certain precision geographical approaches emphasise selection specific areas study interactions spatial characteristics health outcomes sample selected small number specific areas creates statistical challenges observations independent local level results poor statistical validity global level therefore difficult construct sample appropriate geographical probability methodswe used twostage selection procedure first nonrandom stage selection clusters instead randomly selecting clusters deliberately chose group clusters whole would contain variation health measures population health information available survey selected priori determinants influence spatial homogeneity health characteristics method yields distribution variables sample closely resembles overall population something cannot guaranteed randomlyselected clusters especially number selected clusters small way able survey specific areas minimising design effects maximising statistical precisionwe applied strategy health survey carried vientiane lao peoples democratic republic selected wellknown health determinants unequal spatial distribution within city nationality literacy deliberately selected combination clusters whose distribution nationality literacy similar distribution general populationthis paper describes conceptual reasoning behind construction survey sample shows advantageous choose clusters using reasoned hypotheses based probability geographical approaches contrast conventional random cluster selection strategy