Methods for analysis of complex survey data: an application using the Tanzanian 2015 Demographic and Health Survey and Service Provision Assessment

被引:8
|
作者
Sheffel, Ashley [1 ]
Wilson, Emily [1 ]
Munos, Melinda [1 ]
Zeger, Scott [1 ,2 ]
机构
[1] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Int Hlth, Baltimore, MD 21205 USA
[2] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Biostat, Baltimore, MD 21205 USA
关键词
D O I
10.7189/jogh.09.020902
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background Low-income and middle-income countries (LMICs) seek to better utilize household and health facility survey data for monitoring and evaluation, as well as for health program planning. However, analysis of this complex survey data are complicated. In Tanzania, the National Evaluation Platform project sought to analyze Demographic and Health Survey (DHS) data and Service Provision Assessment (SPA) data as part of an evaluation of the national One Plan for Maternal and Child Health. To support this evaluation, we used this survey data to answer two key methodological questions: 1) what are the benefits and costs of using sampling weights in rate estimation; and 2) what is the best method for calculating standard errors in these two surveys? Methods We conducted a simulation study for each methodologic question. The first simulation study assessed the benefits and costs of using sampling weights in rate estimation. This simulation used weighted and unweighted estimates and examined bias, variance, and the mean squared error (MSE). The second simulation study assessed the best method for calculating standard errors comparing cluster bootstrapped variance estimation, design based asymptotic variance with one level (svy1), and design based asymptotic variance with three levels (svy3). We compared coverage probability and confidence interval length. Results Our results showed that although weighted estimates were less biased, unweighted estimates were less variable. The weighted estimates had a lower MSE, indicating that the effect of the bias trade-off was greater than the effect of the variance trade-off for most indicators assessed. The best performer for variance estimation was the cluster bootstrap method, followed by the svy3 method. The svy1 method was the worst performer for most indicators assessed. Conclusions As complex survey data become more widely used for policymaking in LMICs, there is a need for guidance on the best methods for analyzing this data. The standard of practice has been a design-based analysis using survey weights and the single-level svy method for calculating standard errors. This study puts forth an alternative approach to analysis. In addition, this study offers practical guidance on determining the best method for analysis of complex survey data.
引用
收藏
页数:16
相关论文
共 50 条
  • [1] Effective coverage of curative child health services in Ethiopia: analysis of the Demographic and Health Survey and Service Provision Assessment survey
    Haile, Tsegaye Gebremedhin
    Benova, Lenka
    Mirkuzie, Alemnesh H.
    Asefa, Anteneh
    [J]. BMJ OPEN, 2024, 14 (02):
  • [2] Estimation of indices of health service readiness with a principal component analysis of the Tanzania Service Provision Assessment Survey
    Elizabeth F. Jackson
    Ayesha Siddiqui
    Hialy Gutierrez
    Almamy Malick Kanté
    Judy Austin
    James F. Phillips
    [J]. BMC Health Services Research, 15
  • [3] Estimation of indices of health service readiness with a principal component analysis of the Tanzania Service Provision Assessment Survey
    Jackson, Elizabeth F.
    Siddiqui, Ayesha
    Gutierrez, Hialy
    Kante, Almamy Malick
    Austin, Judy
    Phillips, James F.
    [J]. BMC HEALTH SERVICES RESEARCH, 2015, 15
  • [4] Determinants of obstetric fistula in Afghanistan: An analysis of the Demographic and Health Survey 2015
    Yusufi, Mohammad Omid
    Fanning, Erin
    Bhatta, Madhav P.
    [J]. INTERNATIONAL JOURNAL OF GYNECOLOGY & OBSTETRICS, 2022, 159 (01) : 213 - 222
  • [5] Methods of Estimating or Accounting for Neighborhood Associations With Health Using Complex Survey Data
    Brumback, Babette A.
    Cai, Zhuangyu
    Dailey, Amy B.
    [J]. AMERICAN JOURNAL OF EPIDEMIOLOGY, 2014, 179 (10) : 1255 - 1263
  • [6] Association between childhood immunisation coverage and proximity to health facilities in rural settings: a cross-sectional analysis of Service Provision Assessment 2013-2014 facility data and Demographic and Health Survey 2015-2016 individual data in Malawi
    Johns, Nicole E.
    Hosseinpoor, Ahmad Reza
    Chisema, Mike
    Danovaro-Holliday, M. Carolina
    Kirkby, Katherine
    Schlotheuber, Anne
    Shibeshi, Messeret
    Sodha, Samir, V
    Zimba, Boston
    [J]. BMJ OPEN, 2022, 12 (07):
  • [7] Single motherhood in Ghana: analysis of trends and predictors using demographic and health survey data
    Ayebeng, Castro
    Dickson, Kwamena Sekyi
    Seidu, Abdul-Aziz
    Amo-Adjei, Joshua
    [J]. HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS, 2022, 9 (01):
  • [8] Single motherhood in Ghana: analysis of trends and predictors using demographic and health survey data
    Castro Ayebeng
    Kwamena Sekyi Dickson
    Abdul-Aziz Seidu
    Joshua Amo-Adjei
    [J]. Humanities and Social Sciences Communications, 9
  • [9] Role of clusters in exclusive breastfeeding practices in Tanzania: A secondary analysis study using demographic and health survey data (2015/2016)
    Jahanpour, Ola Farid
    Okango, Elphas Luchemo
    Todd, Jim
    Mwambi, Henry
    Mahande, Michael Johnson
    [J]. FRONTIERS IN PEDIATRICS, 2022, 10
  • [10] Determinants of early neonatal mortality in Afghanistan: an analysis of the Demographic and Health Survey 2015
    Al Kibria, Gulam Muhammed
    Burrowes, Vanessa
    Choudhury, Allysha
    Sharmeen, Atia
    Ghosh, Swagata
    Mahmud, Arif
    Angela, K. C.
    [J]. GLOBALIZATION AND HEALTH, 2018, 14