Journal of the Royal Statistical Society: Series A (Statistics in Society)

Cover image for Vol. 180 Issue 2

Edited By: J. Carpenter and H. Goldstein

Impact Factor: 1.702

ISI Journal Citation Reports © Ranking: 2015: 13/49 (Social Sciences Mathematical Methods); 24/123 (Statistics & Probability)

Online ISSN: 1467-985X

Associated Title(s): Journal of the Royal Statistical Society: Series B (Statistical Methodology), Journal of the Royal Statistical Society: Series C (Applied Statistics), Significance

176:1


An examination of the quality and utility of interviewer observations in the National Survey of Family Growth, by B. T. West, Journal of the Royal Statistical Society, Series A, Statistics in Society, Volume 176 (2013), part 1, pages 211–225

RELEVANT PROGRAMS:

Three programs (two SAS programs and one Stata .do file) are included as supplements to this paper. These include:

1. west_jrssa_sascode_final.sas

This SAS program performs the majority of the data management and analyses reported in the paper. This program also creates the data sets used by the other two programs.

2. simulation_code.sas

This SAS program performs the simulations for Research Question #4.

3. stata_comps.do

This Stata program performs the comparisons of the adjusted means for Research Question #3.

NOTE ABOUT NATIONAL SURVEY OF FAMILY GROWTH DATA: The data analyzed for this paper are only available upon special request from the National Center for Health Statistics, and are not publicly available. Interested readers should use these auxiliary programs to understand how the analyses in the paper were conducted.

Brady T. West
Institute for Social Research
Survey Methodology Program
University of Michigan
426 Thompson Street
Ann Arbor
MI 48106
USA

E-mail: bwest@umich.edu

Dataset

Analysing interviewer call record data by using a multilevel discrete time event history modelling approach, by G. B. Durrant, J. D'Arrigo and F. Steele, Journal of the Royal Statistical Society, Series A, Statistics in Society, Volume 176 (2013), part 1, pages 251–269

The file multilevel_multinomial_discretetime_logistic_model_2 contains the aML code for fitting the final model. Access to the data is controlled by the UK Office for National Statistics.

Gabriele B. Durrant
Southampton Statistical Sciences Research Institute
University of Southampton
Highfield
Southampton SO17 1BJ
UK

E-mail: gdurrant@southampton.ac.uk

Dataset (2kb)


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