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Stata and R Code for suppression and homogeneity analyses

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Stata and R code created by Oliver Mills in the Integrated Data Infrastructure environment, as part of his BSc (Hons) project "The Impact Geographical Scales Have on Homogeneity and Suppression", Department of Statistics, The University of Auckland, 2018

These data were also published in the manuscript "Inter-relationships between geographical scale, socio-economic data suppression and population homogeneity" Published in Applied Spatial Analysis and Policy. Article DOI:10.1007/s12061-021-09430-2


The code loads text files (originally sourced from SQL tables of the 2013 Census tables in the IDI), and merges in geographic identifiers for the scales of interest.

Suppression statistics are calculated for Census variables as a dichotomous variable, in which 'suppressed = 1' if a cell count for a variable is fewer than 6.

Homogeneity statistics are calculated using Intra Class Correlations , via the 'estat icc' command following a Multilevel mixed-effects logistic regression.

Analysis was conducted in Stata, and the accompanying R code reshapes and consolidates results for summary analyses as an excel file.

Funding

Health Research Council of New Zealand 13/428 Delivering a new measure of neighbourhood disadvantage for New Zealand

History

Publisher

University of Auckland

Spatial coverage

New Zealand 2013 Census, small area census output geographies

Temporal coverage: start

05/03/2013

Temporal coverage: end

06/03/2018