Row 3763

Row ID: 3763 | Dataset Entry | Axioma AXP Content Repository

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First time dealing with survey data, any help is appreciated. Can I delete the missing observations from data analysis in survey weights application? Over all 15% missing data that includes outcome, exposure, covariates. I researched on imputation methods and spoke with people who worked with NHANES data. Everyone told me that they deleted all the missing information and then performed analysis rather than imputing. I checked regression model with deleting and without deleting the missing information and the odds increased a bit after deleting, however, conclusions are same. Confidence intervals are also wide in both cases (before and after deleting missing data). Any suggestions on the process of survey data analysis, when there is no strata, cluster but only weights application? How to determine if missingness is at random or not in SAS?

FieldValue
text First time dealing with survey data, any help is appreciated. Can I delete the missing observations from data analysis in survey weights application? Over all 15% missing data that includes outcome, exposure, covariates. I researched on imputation methods and spoke with people who worked with NHANES data. Everyone told me that they deleted all the missing information and then performed analysis rather than imputing. I checked regression model with deleting and without deleting the missing infor…
label r/epidemiology
dataType post
communityName r/epidemiology
datetime 2024-03-23
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url_encoded Z0FBQUFBQm5Lak9FOFRNVTVjaFc5YXRVaUY4cEZTWFhnYUlxdFk4RkN0dkFNOFlCd3Z1amhKYkw3eDBxOEpIblpPbnpJU3B3cURJZHhWY1d3bUFZZHRsdjFKeW1ySDA2QXJrdXMwQlV1NFFUc0d4cnhBZVpJZm50ZFV5WUY5ZkNBb3Vwd254ZnBQc0trZHQ0c0gzRDg0ajhqMXFmSVRmMkFnUWwyaXZ5MDRlRHVuS0MzaWpTbWpZN3Jldi1fWC1zZHRSNG5oTXNOenFkMDB5ei1UQVpndUVUWWdLMUU0bm04QT09

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{
  "text": "First time dealing with survey data, any help is appreciated. Can I delete the missing observations from data analysis in survey weights application? Over all 15% missing data that includes outcome, exposure, covariates. I researched on imputation methods and spoke with people who worked with NHANES data. Everyone told me that they deleted all the missing information and then performed analysis rather than imputing. \nI checked regression model with deleting and without deleting the missing information and the odds increased a bit after deleting, however, conclusions are same. Confidence intervals are also wide in both cases (before and after deleting missing data). \nAny suggestions on the process of survey data analysis, when there is no strata, cluster but only weights application? How to determine if missingness is at random or not in SAS? ",
  "label": "r/epidemiology",
  "dataType": "post",
  "communityName": "r/epidemiology",
  "datetime": "2024-03-23",
  "username_encoded": "Z0FBQUFBQm5LakwxdHdKR21NcWFkampyT1pKN3Zpelc0SWZWSW1HYURnSzl5U2hFSGlVN2lUaWhkTXMzXzNwZnBLUTkweE1YWGt3S2RfVmlwaXgyMW9iY1g2S0JpZkVjX0pVWWt2a05UWDdSNEJFWGZuaFNhS1k9",
  "url_encoded": "Z0FBQUFBQm5Lak9FOFRNVTVjaFc5YXRVaUY4cEZTWFhnYUlxdFk4RkN0dkFNOFlCd3Z1amhKYkw3eDBxOEpIblpPbnpJU3B3cURJZHhWY1d3bUFZZHRsdjFKeW1ySDA2QXJrdXMwQlV1NFFUc0d4cnhBZVpJZm50ZFV5WUY5ZkNBb3Vwd254ZnBQc0trZHQ0c0gzRDg0ajhqMXFmSVRmMkFnUWwyaXZ5MDRlRHVuS0MzaWpTbWpZN3Jldi1fWC1zZHRSNG5oTXNOenFkMDB5ei1UQVpndUVUWWdLMUU0bm04QT09"
}
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