Skip to content

peteragao/SMA-SAE

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

9 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

SMA-SAE

This repository contains code for the analyses described in the manuscript "Smoothed Model-Assisted Small Area Estimation" by Peter A. Gao and Jon Wakefield [arXiv].

Data

The following data sources are available upon request online:

  • Data from the 2018 Nigeria DHS can be requested here.

  • Boundary data for Nigeria's administrative divisons (shapeFiles_gadm/) was obtained from the Database of Global Administrative Areas (GADM).

  • Age-specific population density estimates for Nigeria in 2018 were obtained from WorldPop.

  • Poverty rate estimates for Nigeria (nga10povcons200.tif) were obtained from WorldPop.

  • Estimates of accessibility to cities (2015_accessibility_to_cities_v1.0.tif) were obtained from the Malaria Atlas Project.

  • nga_2018_ea_frame_strata_sample_size.csv is a file containing information on number of sampled enumeration areas in each stratum with columns (see Table A.3):

    • DHS: DHS region name
    • GADM: GADM region name
    • Urban: Number of urban EAs sampled
    • Rural: Number of rural EAs sampled

The data should be organized in the following tree structure:

├── data
│   └── Nigeria
│       ├── 2015_accessibility_to_cities_v1.0.tif
│       ├── nga10povcons200.tif
│       ├── nga_2018_poppa.csv
│       ├── nga_f_0_2006.tif
│       ├── nga_f_1_2006.tif
│       ├── nga_f_1_2018.tif
│       ├── nga_m_0_2006.tif
│       ├── nga_m_1_2006.tif
│       ├── nga_m_1_2018.tif
│       ├── nga_ppp_2006_UNadj.tif
│       ├── nga_ppp_2018_UNadj.tif
│       ├── shapeFiles_gadm
│           ├── gadm36_NGA_0.cpg
│           ├── gadm36_NGA_0.dbf
│           ├── gadm36_NGA_0.prj
│           ├── gadm36_NGA_0.shp
│           ├── gadm36_NGA_0.shx
│           ├── gadm36_NGA_1.dbf
│           ├── gadm36_NGA_1.prj
│           ├── gadm36_NGA_1.shp
│           ├── gadm36_NGA_1.shx
│           ├── gadm36_NGA_2.dbf
│           ├── gadm36_NGA_2.prj
│           ├── gadm36_NGA_2.shp
│           ├── gadm36_NGA_2.shx
│           └── license.txt
│       ├── dhsStata
│           └── NGKR7BDT
│               └── NGKR7BFL.DTA
│       └── dhsFlat
│           └── NGGE7BFL
│               ├── NGGE7BFL.cpg
│               ├── NGGE7BFL.dbf
│               ├── NGGE7BFL.prj
│               ├── NGGE7BFL.sbn
│               ├── NGGE7BFL.sbx
│               ├── NGGE7BFL.shp
│               └── NGGE7BFL.shx

Analysis

  • analysis/models.R contains code for implementing the models described in the manuscript.

  • analysis/Nigeria contains scripts for generating Admin-1 level estimates of measles vaccination rates for Nigeria based on the 2018 DHS survey.

    • analysis/Nigeria/process-population-covariates.R generates R objects containing population information for all areas.
    • analysis/Nigeria/Nigeria-MCV-example.R runs analysis and generates figures for the Nigeria example.
  • analysis/simulations contains code for reproducing the simulations described in the manuscript.

Results

Outputs are collected in the results and paper/figures folders.

Notes

The above scripts were run on a cluster computer using R version 4.1.2.

> sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.3 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale:
 [1] LC_CTYPE=C.UTF-8       LC_NUMERIC=C           LC_TIME=C.UTF-8        LC_COLLATE=C.UTF-8     LC_MONETARY=C.UTF-8   
 [6] LC_MESSAGES=C.UTF-8    LC_PAPER=C.UTF-8       LC_NAME=C              LC_ADDRESS=C           LC_TELEPHONE=C        
[11] LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C   

attached base packages:
[1] grid      parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] patchwork_1.1.1    readstata13_0.10.0 SUMMER_1.2.0       raster_3.5-11      rgdal_1.5-28       purrr_0.3.4       
 [7] survey_4.1-1       survival_3.2-13    INLA_21.11.22      foreach_1.5.1      Matrix_1.3-4       spdep_1.2-2       
[13] spData_2.0.1       sp_1.4-6           sf_1.0-5           ggplot2_3.3.5      dplyr_1.0.7        tidyr_1.1.4       

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.8         lattice_0.20-45    deldir_1.0-6       class_7.3-19       assertthat_0.2.1   utf8_1.2.2        
 [7] R6_2.5.1           e1071_1.7-9        pillar_1.6.5       rlang_1.0.0        data.table_1.14.2  splines_4.1.2     
[13] munsell_0.5.0      proxy_0.4-26       compiler_4.1.2     xfun_0.29          pkgconfig_2.0.3    mitools_2.4       
[19] tidyselect_1.1.1   tibble_3.1.6       gridExtra_2.3      codetools_0.2-18   fansi_1.0.2        viridisLite_0.4.0 
[25] crayon_1.4.2       withr_2.4.3        wk_0.5.0           gtable_0.3.0       lifecycle_1.0.1    DBI_1.1.2         
[31] magrittr_2.0.2     units_0.7-2        scales_1.1.1       KernSmooth_2.23-20 cli_3.1.1          viridis_0.6.2     
[37] ellipsis_0.3.2     generics_0.1.1     vctrs_0.3.8        boot_1.3-28        RColorBrewer_1.1-2 s2_1.0.7          
[43] iterators_1.0.13   tools_4.1.2        glue_1.6.1         shadowtext_0.1.1   colorspace_2.0-2   terra_1.4-22      
[49] classInt_0.4-3     knitr_1.37 

About

Smoothed model-assisted small area estimation

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published