This is the data and code repository for the PFAS Public Survey study.
Berthold, A., McCrary A., deVilleneuve, S., Schramm, M. In Submission.
This project uses the renv and targets R packages to facilitate reproducibility. Once the project is downloaded and opened in RStudio install the renv package:
install.packages("renv")
The packages and package versions used in the project can be installed and restored using:
renv::restore()
To reproduce the analysis you will need a Census API key which can be obtained from https://api.census.gov/data/key_signup.html. Then use targets to rerun the analysis. This will take a little while to run:
tidycensus::census_api_key("API KEY GOES HERE")
targets::tar_make()
Survey responses used in our analysis are obtained with:
targets::tar_read(pfas_analysis_data)
## # A tibble: 1,100 Ă— 38
## SEX AGEP RACE5 SCHL RACE2 Q6 Q9_6 Q11_6 Q16 Q17 Q18 Q19_1 Q19_2
## <fct> <fct> <fct> <fct> <fct> <fct> <fct> <fct> <fct> <fct> <dbl> <fct> <fct>
## 1 Male 25:34 Asian Bach… Non-… Filt… No Slig… No I th… 88 Very… Mode…
## 2 Fema… 65+ Whit… High… White Filt… No Slig… No I've… 51 Not … Not …
## 3 Fema… 18:24 Whit… Mast… White Bott… No Not … No I th… 57 Very… Mode…
## 4 Fema… 45:54 Two … Other Non-… Bott… No Extr… Not … I've… 92 Not … Slig…
## 5 Fema… 35:44 Whit… Mast… White Filt… No Mode… Not … I've… 45 Mode… Mode…
## 6 Fema… 35:44 Whit… High… White Bott… No Mode… Not … I th… 62 Slig… Slig…
## 7 Fema… 55:64 Whit… High… White Unfi… No Slig… Not … I've… 33 Not … Slig…
## 8 Fema… 35:44 Blac… High… Non-… Bott… No Very… No I th… 85 Mode… Mode…
## 9 Male 45:54 Two … Doct… Non-… Unfi… No Not … No I've… 44 Very… Slig…
## 10 Fema… 35:44 Blac… High… Non-… Filt… No Mode… No I th… 70 Mode… Slig…
## # â„ą 1,090 more rows
## # â„ą 25 more variables: Q19_3 <fct>, Q19_4 <fct>, Q19_5 <fct>, Q19_6 <fct>,
## # Q19_7 <fct>, Q19_8 <fct>, Q19_9 <fct>, Q19_10 <fct>, Q19_11 <fct>,
## # Q19_12 <fct>, Q19_13 <fct>, Q20_1 <fct>, Q20_2 <fct>, Q20_3 <fct>,
## # Q20_4 <fct>, Q20_5 <fct>, Q20_6 <fct>, Q20_7 <fct>, Q20_8 <fct>,
## # Q20_9 <fct>, Q20_10 <fct>, Q20_11 <fct>, Q20_12 <fct>, Q20_13 <fct>,
## # SEX_NM <fct>
Five models were fit in the analysis:
m1
: Proportional odds model relating self-described knowledge about
PFAS to demographic indicators and community PFAS exposure.
m2
: Summary of 13 proportional odds models relating familiarity of 13
items with potential for PFAS contamination with demographic indicators
and community PFAS exposure.
m3
: Summary of 13 proportional odds models relating intention to
change 13 items with potential for PFAS contamination with demographic
indicators and community PFAS exposure.
m4
: Logistic regression relating awareness of PFAS contamintion in
drinking water with demographics, community PFAS exposure, and drinking
water soruces.
m5
: Proportional odds model relating levels of concern about PFAS in
drinking water with demographics, drinking water sources, and awareness
of drinking water contamination.
Model results can be obtained as follows:
targets::tar_read(m1) |> summary()
## Call:
## svyolr(Q17 ~ SEX + AGEP + RACE2 + SCHL + Q16, design = survey_design)
##
## Coefficients:
## Value Std. Error t value
## SEXFemale -0.007018142 0.1333517 -0.05262881
## SEXOther -0.221628888 0.7350469 -0.30151668
## AGEP25:34 0.319206386 0.2351060 1.35771253
## AGEP35:44 0.488823011 0.2365146 2.06677726
## AGEP45:54 0.032327673 0.2441379 0.13241561
## AGEP55:64 0.087866123 0.2546267 0.34507819
## AGEP65+ -0.057227295 0.2588213 -0.22110740
## RACE2Non-white -0.051615103 0.1487857 -0.34690915
## SCHLHigh school graduate or GED -0.433721051 0.3268952 -1.32678926
## SCHLAssociate degree -0.111914228 0.3444962 -0.32486346
## SCHLBachelor's degree -0.017124060 0.3414690 -0.05014822
## SCHLMaster's degree 0.037258080 0.3634560 0.10251057
## SCHLDoctorate or terminal degree 0.322521674 0.4483818 0.71930145
## SCHLOther 0.442288563 0.4739373 0.93322158
## Q16No -1.267234219 0.1892610 -6.69569515
## Q16Not sure -1.458431421 0.2034316 -7.16914882
##
## Intercepts:
## Value
## I've never heard of it, and don't know what it is|I've heard of it or seen it somewhere, but don't know what it is -1.5097
## I've heard of it or seen it somewhere, but don't know what it is|I think I know what it is 0.0109
## I think I know what it is|I'm confident I know what it is 1.6546
## Std. Error
## I've never heard of it, and don't know what it is|I've heard of it or seen it somewhere, but don't know what it is 0.4048
## I've heard of it or seen it somewhere, but don't know what it is|I think I know what it is 0.4074
## I think I know what it is|I'm confident I know what it is 0.4243
## t value
## I've never heard of it, and don't know what it is|I've heard of it or seen it somewhere, but don't know what it is -3.7300
## I've heard of it or seen it somewhere, but don't know what it is|I think I know what it is 0.0268
## I think I know what it is|I'm confident I know what it is 3.8991
## (18 observations deleted due to missingness)
m1
and m2
require some tidying:
## each model is a row 1:13:
targets::tar_read(m2)$m[[1]] |> summary()
## Call:
## svyolr(as.formula(fmla), design = survey_design)
##
## Coefficients:
## Value Std. Error t value
## SEXFemale -0.0002686932 0.1342515 -0.002001416
## SEXOther -0.1002121412 0.3006684 -0.333297874
## AGEP25:34 -0.0405191544 0.2477934 -0.163519889
## AGEP35:44 0.0596672008 0.2430864 0.245456775
## AGEP45:54 -0.4067048355 0.2612073 -1.557019242
## AGEP55:64 -0.8046801762 0.2623818 -3.066829411
## AGEP65+ -1.2102407808 0.2785606 -4.344622670
## RACE2Non-white -0.0289145971 0.1518353 -0.190433898
## SCHLHigh school graduate or GED -0.1365255724 0.3482390 -0.392045626
## SCHLAssociate degree -0.2093106437 0.3646580 -0.573991686
## SCHLBachelor's degree 0.1871257068 0.3540321 0.528555725
## SCHLMaster's degree 0.8071510356 0.3814651 2.115923565
## SCHLDoctorate or terminal degree 0.5933868716 0.5193126 1.142639142
## SCHLOther 0.0942200283 0.4541967 0.207443217
## Q16No -1.4256779239 0.1922047 -7.417496885
## Q16Not sure -2.0106256160 0.1991107 -10.098027107
##
## Intercepts:
## Value Std. Error t value
## Not at all familiar|Slightly familiar -2.2146 0.4343 -5.0994
## Slightly familiar|Moderately familiar -1.2421 0.4335 -2.8651
## Moderately familiar|Very familiar -0.1139 0.4330 -0.2629
## Very familiar|Extremely familiar 0.9026 0.4374 2.0636
## (18 observations deleted due to missingness)
renv::diagnostics()
## Diagnostics Report [renv 1.0.0]
## ===============================
##
## # Session Info ---------------------------------------------------------------
## R version 4.3.1 (2023-06-16 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 11 x64 (build 22621)
##
## Matrix products: default
##
##
## locale:
## [1] LC_COLLATE=English_United States.utf8
## [2] LC_CTYPE=English_United States.utf8
## [3] LC_MONETARY=English_United States.utf8
## [4] LC_NUMERIC=C
## [5] LC_TIME=English_United States.utf8
##
## time zone: America/Chicago
## tzcode source: internal
##
## attached base packages:
## [1] grid stats graphics grDevices datasets utils methods
## [8] base
##
## other attached packages:
## [1] survey_4.2-1 survival_3.5-5 Matrix_1.4-1
##
## loaded via a namespace (and not attached):
## [1] base64url_1.4 dplyr_1.1.1 compiler_4.3.1 renv_1.0.0
## [5] tidyselect_1.2.0 callr_3.7.3 splines_4.3.1 yaml_2.3.7
## [9] fastmap_1.1.1 lattice_0.20-45 R6_2.5.1 generics_0.1.3
## [13] igraph_1.4.2 knitr_1.42 backports_1.4.1 targets_1.0.0
## [17] tibble_3.2.1 DBI_1.1.3 pillar_1.9.0 rlang_1.1.0
## [21] utf8_1.2.3 xfun_0.38 cli_3.6.1 withr_2.5.0
## [25] magrittr_2.0.3 ps_1.7.4 digest_0.6.31 processx_3.8.0
## [29] rstudioapi_0.14 lifecycle_1.0.3 vctrs_0.6.1 evaluate_0.20
## [33] glue_1.6.2 data.table_1.14.8 codetools_0.2-18 mitools_2.4
## [37] fansi_1.0.4 rmarkdown_2.21 tools_4.3.1 pkgconfig_2.0.3
## [41] htmltools_0.5.5
##
## # Project --------------------------------------------------------------------
## Project path: "C:/Data-Analysis-Projects/pfas-survey"
##
## # Status ---------------------------------------------------------------------
## No issues found -- the project is in a consistent state.
##
## # Packages -------------------------------------------------------------------
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