Abstract
This study aimed to describe the estimated means for weight, height, and body mass index (BMI) according to two imputation methods, using data from Vigitel (Risk and Protective Factors Surveillance System for Chronic Non-Communicable Diseases Through Telephone Interview). This was a cross-sectional study that used secondary data from the Vigitel survey from 2006 to 2017. The two imputation methods used in the study were hot deck and Predictive Mean Matching (PMM). The weight and height variables imputed by hot deck were provided by Vigitel. Two models were conducted with PMM: (i) explanatory variables - city, sex, age in years, race/color, and schooling; (ii) explanatory variables - city, sex, and age in years. Weight and height were the outcome variables in the two models. PMM combines linear regression and random selection of the value for imputation. Linear prediction is used as a measure of distance between the missing value and the possible donors, thereby creating the virtual space with the candidate cases for yielding the value for imputation. One of the candidates from the pool is randomly selected, and its value is assigned to the missing unit. BMI was calculated by dividing weight in kilograms by height squared. The result shows the means and standard deviations for weight, height, and BMI according to imputation method and year. The estimates used the survey module from Stata, which considers the sampling effects. The mean values for weight, height, and BMI estimated by hot deck and PMM were similar. The results with the Vigitel data suggest the applicability of PMM to the set of health surveys.
Highlights
This study aimed to describe the estimated means for weight, height, and body mass index (BMI) according to two imputation methods, using data from Vigitel (Risk and Protective Factors Surveillance System for Chronic Non-Communicable Diseases Through Telephone Interview)
Imputation by predictive mean matching: promise & peril. https://statistic alhorizons.com/predictive-mean-matching (acessado em 12/Jan/2020)
Summary
O objetivo deste estudo foi descrever a estimativa das médias de peso, altura e índice de massa corporal (IMC) segundo dois métodos de imputação, usando dados do Vigitel (Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por Inquérito Telefônico). Considerando a ausência de clareza metodológica em relação à imputação por hot deck na publicação do Vigitel e a disponibilidade do método PMM em diversos pacotes estatísticos, o objetivo deste estudo foi descrever a estimativa das médias de peso, altura e índice de massa corporal (IMC) segundo dois métodos de imputação, usando dados do Vigitel. O segundo modelo foi elaborado considerando a perspectiva de que, para a imputação de uma variável, as covariáveis não devem possuir valores faltantes e, portanto, foram selecionadas apenas com resposta para todos os indivíduos: cidade, sexo e idade em anos. Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por Inquérito Telefônico (Vigitel), 2006 a 2017
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