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Attrition analysed in five waves of a longitudinal yearly survey of smokers: findings from the ITC Netherlands survey

机译:在对吸烟者纵向年度调查的五大浪潮中分析的消耗:ITC荷兰调查的调查结果

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Background: Attrition bias can affect the external validity of findings. This article analyses attrition bias and assesses the effectiveness of replenishment samples on demographic and smoking-related characteristics for the International Tobacco Control Netherlands Survey, a longitudinal survey among smokers. Methods: Attrition analyses were conducted for the first five survey waves (2008-12). We assessed, including and excluding replenishment samples, whether the demographic composition of the samples changed between the first and fifth waves. Replenishment samples were tailored to ensure the sample remained representative of the smoking population. We also constructed a multivariable survival model of attrition that included all five waves with replenishment samples. Results: Of the original 1820 respondents recruited in 2008, 46% participated again in 2012. Demographic differences between waves due to attrition were generally small and replenishment samples tended to minimize them further. The multivariable survival analysis revealed that only two of the 10 variables analysed were significant predictors of attrition: a weak effect for gender (men dropped out more often) and weak to moderate effects for age (respondents aged 15-24 years dropped out more than aged 25-39 years, who dropped out more than those aged 40+ years). Conclusions: Weak to moderate attrition effects were found for men and younger age groups. This information could be used to minimize respondent attrition. Our findings suggest that sampling weights and tailored replenishment samples can effectively compensate for attrition effects. This is already being done for the International Tobacco Control Netherlands Survey, including the categories that significantly predicted attrition in this study.
机译:背景:磨损偏差会影响调查结果的外部有效性。本文分析了消磨偏见,评估了补充样本对国际烟草控制荷兰调查的人口和吸烟有关的有效性,吸烟者的纵向调查。方法:对前五个调查波进行的磨损分析(2008-12)进行。我们评估,包括和排除补充样品,是否在第一和第五波之间改变样品的人口统计组成。补充样品量身定制,以确保样品仍然代表吸烟人群。我们还构建了一种多变量的磨损模型,包括所有五波与补充样品。结果:2008年招聘的原始1820名受访者,46%在2012年再次参加。由于磨损导致的海浪之间的人口统计学差异通常很小,补充样品倾向于进一步减少它们。多变量的存活分析显示,分析的10个变量中只有两个是磨损的重要预测因子:性别(男性频繁地下降的弱势)和年龄较小的中度效果弱(15-24岁的受访者降低超过年龄25-39岁,谁放弃了超过40岁以上的人)。结论:为男性和较年轻的年龄群体发现了弱于中等的磨损效果。这些信息可用于最小化受访者的磨损。我们的研究结果表明,取样权重和量身定制的补充样品可以有效地补偿磨损效果。这已经是为国际烟草控制荷兰调查而完成的,包括本研究中显着预测磨损的类别。

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