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  1. 11/paper.pdf +3 -0
  2. 11/replication_package/ChangingHearts_GublerEtAl_Appendix_Update.pdf +3 -0
  3. 11/replication_package/README_Update.txt +3 -0
  4. 11/replication_package/Replication/Data/.Rapp.history +1 -0
  5. 11/replication_package/Replication/Data/pretest-1.RData +3 -0
  6. 11/replication_package/Replication/Data/pretest-1.csv +3 -0
  7. 11/replication_package/Replication/Data/pretest.RData +3 -0
  8. 11/replication_package/Replication/Data/pretest.csv +3 -0
  9. 11/replication_package/Replication/Data/stud01_deID-1.RData +3 -0
  10. 11/replication_package/Replication/Data/stud01_deID-1.csv +3 -0
  11. 11/replication_package/Replication/Data/stud01_deID.RData +3 -0
  12. 11/replication_package/Replication/Data/stud01_deID.csv +3 -0
  13. 11/replication_package/Replication/Data/stud02_deID-1.csv +3 -0
  14. 11/replication_package/Replication/Data/stud02_deID.RData +3 -0
  15. 11/replication_package/Replication/Data/stud02_deID.csv +3 -0
  16. 11/replication_package/Replication/README.txt +3 -0
  17. 11/replication_package/Replication/ReplicationScript/.Rhistory +6 -0
  18. 11/replication_package/Replication/ReplicationScript/ChangingHearts_GublerEtAl_Jul2021-1.R +0 -0
  19. 11/replication_package/Replication/ReplicationScript/ChangingHearts_GublerEtAl_Jul2021.R +0 -0
  20. 11/replication_package/Replication/ReplicationScript/ChangingHearts_GublerEtAl_Jul2021_log-1.pdf +3 -0
  21. 11/replication_package/Replication/ReplicationScript/ChangingHearts_GublerEtAl_Jul2021_log.pdf +3 -0
  22. 11/replication_package/Replication/code_flowchart/appendix_flowchart_study2.R +104 -0
  23. 11/replication_package/Replication/code_flowchart/stud02_post.csv +3 -0
  24. 11/replication_package/Replication/code_flowchart/stud02_pre.csv +3 -0
  25. 11/replication_package/stud02_deID.RData +3 -0
  26. 11/should_reproduce.txt +3 -0
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11/replication_package/Replication/ReplicationScript/ChangingHearts_GublerEtAl_Jul2021-1.R ADDED
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11/replication_package/Replication/ReplicationScript/ChangingHearts_GublerEtAl_Jul2021.R ADDED
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11/replication_package/Replication/code_flowchart/appendix_flowchart_study2.R ADDED
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+
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+ ## This is code to take the full dataset and produce the numbers in the
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+ ## flowchart for study 2 in the appendix
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+
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+ library(tidyverse)
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+ library(haven)
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+ library(data.table)
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+
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+ ## Can set your working directory here to the folder
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+ setwd("~/Dropbox/GKMR/PapersPresentations/2020Submission/Additions_PostReplication/code")
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+
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+ ## Read in the pre and post data and the one used in the replication
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+ s02post <- read_csv("stud02_post.csv") %>% as.data.table()
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+ s02pre <- read_csv("stud02_pre.csv") %>% as.data.table()
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+
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+ ## Change names to allow distinguishing pre- from post- variables
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+ setnames(s02pre, paste0("pre_", names(s02pre)))
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+ setnames(s02pre, "pre_Voter ID", "Voter_ID") #but keep the merging var the same
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+
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+ ## Remove the one duplicated respondent
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+ s02pre <- s02pre[!(duplicated(Voter_ID))]
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+
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+ ## Number invited to the wave 2 survey
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+ nrow(s02pre)
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+ ## [1] 3623
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+
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+ ## Combine
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+ setkey(s02pre, "Voter_ID")
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+ setkey(s02post, "Voter_ID")
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+ s02comb <- s02pre[s02post]
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+
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+ ## Create the treatment condition variable
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+ ## First for those in control
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+ myvars <- str_subset(names(s02comb), "PositiveLegal")
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+ myvars
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+ ## [1] "FL_238_DO_PositiveLegal" "FL_268_DO_PositiveLegal"
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+ ## [3] "FL_265_DO_PositiveLegal" "FL_262_DO_PositiveLegal"
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+ s02comb[, condition := NA_integer_]
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+ s02comb[rowSums(s02comb[, ..myvars], na.rm = TRUE) == 1, condition := 0]
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+ ## Now for those in treatment
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+ myvars <- str_subset(names(s02comb), "PositiveIllegal")
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+ ## [1] "FL_238_DO_PositiveIllegal" "FL_268_DO_PositiveIllegal"
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+ ## [3] "FL_265_DO_PositiveIllegal" "FL_262_DO_PositiveIllegal"
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+ s02comb[rowSums(s02comb[, ..myvars], na.rm = TRUE) == 1, condition := 1]
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+
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+ ## Number that didn't respond is difference between the pre and combined surveys
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+ nrow(s02pre)
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+ ## [1] 3623
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+ nrow(s02comb)
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+ ## [1] 2632
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+ nrow(s02pre) - nrow(s02comb)
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+ ## [1] 991
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+
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+ ## There are also people in this dataset who finished/started taking the survey
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+ ## after it closed; eliminate those here
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+ nrow(s02comb)
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+ ## [1] 2632
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+ s02comb <- s02comb[as.POSIXct(EndDate) < as.POSIXct("2015-09-16 16:05:00 MDT")]
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+ nrow(s02comb)
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+ ## [1] 2399
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+ 2632 - 2399 #233 removed for this reason
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+
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+ ## How many in each condition now?
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+ table(s02comb$condition, useNA = "ifany")
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+ ## 0 1 <NA>
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+ ## 1065 1062 272
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+
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+ ## Remove the 272 respondents who were never assigned to a treatment condition
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+ s02comb <- s02comb[!is.na(condition)]
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+ nrow(s02comb) #new n-size is 2127
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+
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+ ## Who did not finish the survey?
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+ table(s02comb$condition, s02comb$Finished, useNA = "ifany")
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+ ## 0 1
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+ ## 0 8 1057
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+ ## 1 9 1053
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+ ## 8 in control and 9 in treatment that didn't finish
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+
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+ ## Remove those who did not finish the survey
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+ s02comb <- s02comb[Finished == 1]
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+ nrow(s02comb) #new n-size is 2110
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+
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+ ## What about non-whites/Latinos?
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+ ## In this raw dataset, this is asked in the question pre_Q58
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+ table(s02comb$pre_Q58, useNA = "ifany")
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+ ## 1 2 3 4 5 6 7 8 <NA>
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+ ## 3 10 3 44 1977 14 14 40 5
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+
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+ ## Everyone labeled as a 5 is white, so look at 5 vs other
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+ table(s02comb$condition, as.integer(s02comb$pre_Q58 == 5), useNA = "ifany")
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+ ## 0 1 <NA>
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+ ## 0 74 978 5
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+ ## 1 54 999 0
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+ ## 74 in control and 54 in treatment that are non-white or Latino - for the NAs,
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+ ## keep those in (which in effect assumes that they are white)
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+
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+ ## Remove those who are non-white or Latino
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+ s02comb <- s02comb[!(pre_Q58 %in% c(1:4, 6:8))]
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+ nrow(s02comb) #new n-size is 1982
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+ table(s02comb$condition, useNA = "ifany")
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+ ## 0 1
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+ ## 983 999
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+ ## This gives us numbers that correspond to the final row of the flowchart
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+ ## in the appendix
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