Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Inglehart says shaky job market for millennials has contributed to their disaffection

Stephenson says homophobia among gay men raises risk of intimate partner violence

Frey says having more immigrants with higher birth rates fills need in the US

More News

Highlights

Savolainen wins Outstanding Contribution Award for study of how employment affects recidivism among past criminal offenders

Giving Blueday at ISR focuses on investing in the next generation of social scientists

Pfeffer and Schoeni cover the economic and social dimensions of wealth inequality in this special issue

PRB Policy Communication Training Program for PhD students in demography, reproductive health, population health

More Highlights

Next Brown Bag

Mon, Jan 23, 2017 at noon:
H. Luke Shaefer

The Us National Comorbidity Survey Replication (Ncs-R) Design and Field Procedures

Publication Abstract

Kessler, R.C., P. Berglund, W.T. Chiu, O. Demler, Steven Heeringa, E. Hiripi, R. Jin, B.E. Pennell, E.E. Walters, A. Zaslavsky, and H. Zheng. 2004. "The Us National Comorbidity Survey Replication (Ncs-R) Design and Field Procedures." International Journal of Methods in Psychiatric Research, 13:69-92.

The National Comorbidity Survey Replication (NCS-R) is a survey of the prevalence and correlates of mental disorders in the US that was carried out between February 2001 and April 2003. Interviews were administered face-to-face in the homes of respondents, who were selected from a nationally representative multi-stage clustered area probability sample of households. A total of 9,282 interviews were completed in the main survey and an additional 554 short non-response interviews were completed with initial non-respondents. This paper describes the main features of the NCS-R design and field procedures, including information on fieldwork organization and procedures, sample design, weighting and considerations in the use of design-based versus model-based estimation. Empirical information is presented on non-response bias, design effect, and the trade-off between bias and efficiency in minimizing total mean-squared error of estimates by trimming weights.

Browse | Search : All Pubs | Next