| Titre : | Handling Nonresponse in Surveys : Analytic Corrections Compared with Converting Nonresponders. (2008) |
| Auteurs : | Paul JENKINS ; Patrick BURDICK ; Giulia EARLE-RICHARDSON ; John MAY ; Bassett Research Institute. Cooperstown. NY. USA ; New York Center for Agricultural Medicine and Health. Cooperstown. NY. USA |
| Type de document : | Article |
| Dans : | American journal of epidemiology (vol. 167, n° 3, 2008) |
| Pagination : | 369-374 |
| Langues: | Anglais |
| Mots-clés : | Enquête épidémiologique ; Enquête ; Surveillance ; Etude comparée ; Biais ; Collecte information ; Prélèvement ; Statistique ; Epidémiologie ; Homme |
| Résumé : | [BDSP. Notice produite par INIST-CNRS R0xhEMz2. Diffusion soumise à autorisation]. A large health survey was combined with a simulation study to contrast the reduction in bias achieved by double sampling versus two weighting methods based on propensity scores. The survey used a census of one New York county and double sampling in six others. Propensity scores were modeled as a logistic function of demographic variables and were used in conjunction with a random uniform variate to simulate response in the census. These data were used to estimate the prevalence of chronic disease in a population whose parameters were defined as values from the census. Significant (p<0.0001) predictors in the logistic function included multiple (vs. single) occupancy (odds ratio (OR)=1.3), bank card ownership (OR=2.1), gender (OR=1.5), home ownership (OR=1.3), head of household's age (OR=1.4), and income>$18,000 (OR=0.8). The model likelihood ratio chi-square was significant (p<0.0001), with the area under the receiver operating characteristic curve=0.59. Double-sampling estimates were marginally closer to population values than those from either weighting method. However, the variance was also greater (p<0.01). The reduction in bias for point estimation from double sampling may be more than offset by the increased variance associated with this method. |
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