Volume 16, Issue 5 (1-2018)
TB 2018, 16(5): 65-76 |
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fallahzade H, saberi F, najjarzade A, saberi Z. Study the Effect of Different Doses of Vitamin D Supplementation in Insulin Resistance During Women' s Pregnancy with Missing Data. TB 2018; 16 (5) :65-76
URL: http://tbj.ssu.ac.ir/article-1-1300-en.html
URL: http://tbj.ssu.ac.ir/article-1-1300-en.html
, farzanehsaberi12@gmail.com
Abstract: (2931 Views)
Introduction: The aim of this study was to impute missing data and to compare the effect of different doses of vitamin D supplementation on insulin resistance during pregnancy.
Methods: A clinical trial study was done on 104 women with diabetes and gestational age less than 12 weeks between 1391 and 1393. These subjects were randomly divided into three groups; pregnant women who received daily 200 IU vitamin D (group A), women where receiving monthly 50,000 IU vitamin D (Group B) and Group C are women who received 50,000 IU vitamins D every two weeks. In order to investigate the effect of missing data, the data were studied in two ways, with and without considering missing data. To analyze data in the presence of missing observations, the mechanism of MCAR is considered as the missing mechanism. Then, in order to impute the missing data, four methods including mean imputation, random overall hot-deck imputation, within-class random hot-deck imputation and nearest neighbor imputation was used.
Results: In this study, in random overall hot-deck imputation, the difference between blood sugar and insulin resistance variables are not normal, so median and their interquartile range were reported in the table. Furthermore, kruskal-wallis test was used to compare 3 groups variables. The difference insulin resistance variable was not normal in the nearest neighbor imputation method, so the median and interquartile range was reported in the table. In addition, the kruskal-wallis test was used to compare 3 groups of data. The delta index was calculated for all imputation methods.
Conclusion: In this study, delta index was calculated to evaluate and to compare imputation methods. The random overall hot-deck imputation was described as the best imputation method.
Methods: A clinical trial study was done on 104 women with diabetes and gestational age less than 12 weeks between 1391 and 1393. These subjects were randomly divided into three groups; pregnant women who received daily 200 IU vitamin D (group A), women where receiving monthly 50,000 IU vitamin D (Group B) and Group C are women who received 50,000 IU vitamins D every two weeks. In order to investigate the effect of missing data, the data were studied in two ways, with and without considering missing data. To analyze data in the presence of missing observations, the mechanism of MCAR is considered as the missing mechanism. Then, in order to impute the missing data, four methods including mean imputation, random overall hot-deck imputation, within-class random hot-deck imputation and nearest neighbor imputation was used.
Results: In this study, in random overall hot-deck imputation, the difference between blood sugar and insulin resistance variables are not normal, so median and their interquartile range were reported in the table. Furthermore, kruskal-wallis test was used to compare 3 groups variables. The difference insulin resistance variable was not normal in the nearest neighbor imputation method, so the median and interquartile range was reported in the table. In addition, the kruskal-wallis test was used to compare 3 groups of data. The delta index was calculated for all imputation methods.
Conclusion: In this study, delta index was calculated to evaluate and to compare imputation methods. The random overall hot-deck imputation was described as the best imputation method.
Keywords: Insulin resistance, Gestational Diabetes, Missing data, Imputation, Hot –deck Imputation, Missing Completely at Random, .Missing at Random, Missing Not at Random
Type of Study: Research |
Subject:
Special
Received: 2015/01/20 | Accepted: 2015/03/9 | Published: 2018/01/20
Received: 2015/01/20 | Accepted: 2015/03/9 | Published: 2018/01/20
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