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http://dx.doi.org/10.4163/kjn.2012.45.6.600

Complex sample design effects and inference for Korea National Health and Nutrition Examination Survey data  

Chung, Chin-Eun (Department of Food and Nutrition, Ansan University)
Publication Information
Journal of Nutrition and Health / v.45, no.6, 2012 , pp. 600-612 More about this Journal
Abstract
Nutritional researchers world-wide are using large-scale sample survey methods to study nutritional health epidemiology and services utilization in general, non-clinical populations. This article provides a review of important statistical methods and software that apply to descriptive and multivariate analysis of data collected in sample surveys, such as national health and nutrition examination survey. A comparative data analysis of the Korea National Health and Nutrition Examination Survey (KNHANES) was used to illustrate analytical procedures and design effects for survey estimates of population statistics, model parameters, and test statistics. This article focused on the following points, method of approach to analyze of the sample survey data, right software tools available to perform these analyses, and correct survey analysis methods important to interpretation of survey data. It addresses the question of approaches to analysis of complex sample survey data. The latest developments in software tools for analysis of complex sample survey data are covered, and empirical examples are presented that illustrate the impact of survey sample design effects on the parameter estimates, test statistics, and significance probabilities (p values) for univariate and multivariate analyses.
Keywords
Korea National Health and Nutrition Examination Survey (KNHANES); sample design; design effect; stratification; clustering; weighting; sampling variance;
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  • Reference
1 Kish L, Groves RM, Krotki KP. World fertility survey. Sampling errors for fertility surveys. In: Occasional Paper, No. 17. Voorburg: International Statistical Institute; 1975
2 Agresti A. Categorical data analysis, 2nd edition. New York: John Wiley & Sons; 2002
3 Agresti A. An introduction to categorical data analysis, 2nd edition. New York: John Wiley & Sons; 2007
4 Lee JH, Moon IO, Chung CE. Health statistics. Seoul: Power Book Co.; 2008
5 Roberts G, Rao JNK, Kumar S. Logistic regression analysis of sample survey data. Biometrika 1987; 74(1): 1-12   DOI   ScienceOn
6 Morel JG. Logistic regression under complex survey designs. Surv Methodol 1989; 15: 203-223
7 Hosmer DW Jr, Lemeshow S. Applied logistic regression, 2nd edition. New York: John Wiley & Sons; 2000
8 Cochran WG. Sampling techniques. New York: John Wiley & Sons; 1977
9 Skinner CJ, Holt D, Smith TMF. Analysis of complex surveys. New York: John Wiley & Sons; 1989
10 Sarndal CE, Swensson B, Wretman J. Model assisted survey sampling. New York: Springer; 1992
11 Binder DA, Roberts GR. Design-based and model-based methods for estimating model parameters. In: Analysis of Survey Data. New York: John Wiley & Sons; 2003
12 Fuller WA. Sampling statistics. Hoboken: John Wiley & Sons; 2009
13 SPSS. Armonk: IBM; 2012. Available from: http://www.spss.com
14 SUDAAN version 11. Research Triangle Park: RTI International; 2011
15 Lohr SL. Sampling: design and analysis, 2nd edition. Boston: Brooks/Cole; 2010
16 Kish L. Survey sampling. New York: John Wiley & Sons; 1965
17 Goldstein H. Multi-level models in educational and social research. London: Oxford University Press; 1987
18 Rust K. Variance estimation for complex estimators in sample surveys. J Off Stat 1985; 1(4): 381-397
19 Wolter KM. Introduction to variance estimation. New York: Springer; 1985
20 Woodruff RS. A simple method for approximating the variance of a complicated estimate. J Am Stat Assoc 1971: 66(334): 411-414   DOI   ScienceOn
21 Ministry of Health and Welfare. Korea National Health and Nutrition Examination Survey. Seoul: Ministry of Health and Welfare. Available from: http://knhanes.cdc.go.kr
22 Heeringa SG, Liu J. Complex sample design effects and inference for mental health survey data. Int J Methods Psychiatr Res 1998; 7(1): 56-65   DOI   ScienceOn
23 Muthen BO, Satorra A. Complex sample data in structural equation modeling. Sociol Methodol 1995; 25: 267-316   DOI
24 Koch GG, Lemeshow S. An application of multivariate analysis to complex sample survey data. In: Institute of Statistics Mimeo Series No. 802. Chapel Hill: University of North Carolina; 1972
25 Chung CE. Evaluation of statistical methodology in national journals related with food science, cooking, and food culture. Seoul: Youlchon Foundation; 2010. p.591-703
26 SAS version 9.3. Cary: SAS Institute Inc.; 2011. Available from: http://www.sas.com
27 Kish L, Frankel MR. Balanced repeated replications for standard errors. J Am Stat Assoc 1970; 65(331): 1071-1094   DOI   ScienceOn
28 Rao JNK, Shao J. Modified balanced repeated replication for complex survey data. Biometrika 1999; 86(2): 403-415   DOI   ScienceOn
29 Rao JNK, Wu CFJ. Resampling inference with complex survey data. J Am Stat Assoc 1988; 83(401): 231-241   DOI   ScienceOn
30 Rao JNK, Wu CFJ, Yue K. Some recent work on resampling methods for complex surveys. Surv Methodol 1992; 18: 209-217
31 Williams RL. A note on robust variance estimation for clustercorrelated data. Biometrics 2000; 56(2): 645-646   DOI   ScienceOn
32 Wolter KM. Introduction to variance estimation, 2nd edition. New York: Springer; 2007
33 Stata Corp. Stata statistical software: release 5. College Station: Stata Corp.; 1997
34 Brick JM, Broene P, James P, Severynse J. A user's guide to Wes- Var PC. Rockville: Westat Inc.; 1996