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调查研究中数据缺失的机制及处理方法 被引量：11

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作者 周艺彪 姜庆五 赵根明
机构地区 复旦大学公共卫生学院流行病学教研室
出处 《中国卫生统计》 CSCD 北大核心 2005年第5期318-321,共4页 Chinese Journal of Health Statistics
基金 国家自然科学基金重点项目(39930160)
关键词 数据缺失 处理方 收集方法 缺失数据 调查项目 查对 无应答 放弃
分类号 R195 [医药卫生—卫生统计学] R47 [医药卫生—护理学]
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参考文献21

  • 1Streiner DL,Finkle WD.The case of the missing Data:Methods of dealing with dropouts and other research vagaries.Can J Psychiatry,2002,47(1):68-75.
  • 2Huisman M,Krol B,Sonderen EV.Handling missing data by re-approaching non-respondent.Quality & quantity,1998,32(1):77-91.
  • 3Graham JW,Donaldson SI.Evaluating interventions with differential attrition: The importance of non-response mechanisms and follow-up data.J Applied Psychology,1993,78(1):119-128.
  • 4Velsor-Friedrich B.Srof B.Asthma self-management programs for children.Part I: Description of the programs.J Child Fam Nurs,2000,3(1):85-97.
  • 5Taylor JM,Cooper KL,Wei JT,et al.Use of multiple imputation to correct for nonresponse bias in a survey of urologic symptoms and African-American men.Am J Epidemiol,2002,156(8):774-782.
  • 6Rubin DB.Multiple imputation for nonresponse in surveys.New York: John Wiley& Sons,Inc.1987,53.
  • 7Pigott TD.A review of methods for missing data.Educational research and Evaluation[J].2001,7(4):353-383.
  • 8Jones MP.Indicator and stratification methods for missing explanatory variables in multiple linear regression.J Am Stat Assoc,1996,91(433):222-230.
  • 9Little RJA.A test of missing completely at random for multivariate data with missing values.J Am Stat Assoc,1988,83(404):1198-1202.
  • 10Kmetic A,Joseph L,Berger C,et al.Multiple imputation to account for missing data in a survey: estimating the prevalence of osteoporosis.Epidemiol,2002,13(4):437-444.

二级参考文献16

  • 1Austin MA, Criqui MH, Barrett-Connor E, et al. The effect of response bias on odds ratio. Am J Epidemiol, 1981, 114:137-143.
  • 2Subar AF, Ziegler RG, Thompson FE, et al. Is shorter always better? Relative importance of questionnaire length and cognitive ease on response rates and data quality for two dietary questionnaires. Am J Epidemiol, 2001, 153:404-409.
  • 3Taylor JM, Cooper KL, Wei JT,et al. Use of multiple imputation to correct for nonresponse bias in a survey of urologic symptoms among African-American men. Am J Epidemiol, 2002, 156:774-782.
  • 4Pigott TD. A review of methods for missing data. Edu Res Evaluation,2001,7:353-383.
  • 5Raghunathan TE, Lepkowski JM, Van Hoewyk J, et al. A multivariate technique for multiply imputing missing values using a sequence of regression models. Surv Methodol, 2001,27:85-95.
  • 6Fay RE. Alternative paradigms for the analysis of imputed survey data. J AM Stat Assoc, 1996,91:490-498.
  • 7Kmetic A, Joseph L, Berger C, et al. Multiple imputation to account for missing data in a survey: estimating the prevalence of osteoporosis. Epidemiology, 2002,13:437-444.
  • 8Heitjan DF. Annotation: what can be done about missing data? Approaches to imputation. Am J Public Health, 1997,87:548-550.
  • 9Rubin DB. Multiple imputation for nonresponse in surveys. New York: John Wiley & Sons, Inc., 1987. 53.
  • 10Rubin DB. Multiple imputation after 18+ years. J Am Stat Assoc, 1996, 91:473-489.

共引文献14

同被引文献116

引证文献11

二级引证文献42

中国卫生统计
2005年 第5期

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