Open AccessThe Saudi National Mental Health Survey: Sample design and weight development
Author(s) -
Mneimneh Zei.,
Heeringa Steven G.,
Lin YuChieh,
Altwaijri Yasmin A.,
Nishimura Raphael
Publication year - 2020
Publication title -
international journal of methods in psychiatric research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.275
H-Index - 73
eISSN - 1557-0657
pISSN - 1049-8931
DOI - 10.1002/mpr.1829
Subject(s) - weighting , sample (material) , proxy (statistics) , estimation , survey sampling , statistics , selection bias , sampling design , mental health , survey methodology , population , sample size determination , cluster analysis , computer science , psychology , environmental health , mathematics , medicine , engineering , chemistry , systems engineering , chromatography , psychotherapist , radiology
Objectives To describe the sample design and weighting procedures used in the Saudi National Mental Health Survey (SNMHS). Methods A multistage clustered area probability design was used to select the SNMHS sample with one male and one female KSA citizen ages 15–65 surveyed in each sample household. Results A design representative of the household population was developed and modified iteratively to adjust for unanticipated field complications. These modifications, along with variation in within‐household probabilities of selection and geographic–demographic variation in response rates were accounted for through survey weights. Design‐based estimation methods were used to adjust for the effects of these weights and of geographic clustering. Design effects were estimated and simulations were carried out on bias‐variancetrade‐offs in weight trimming to evaluate the implication of design features for precision of estimates. Conclusions The multiple purposes of the survey will require the use of different weights for different types of analyses, including household and person weights as well as weights for proxy reports about household members whose disabilities prevented them from participating in the survey. It will be important to use these different weights appropriately in the diverse analyses that will be undertaken with the SNMHS data.