63 lines
2.4 KiB
R
63 lines
2.4 KiB
R
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library(knitr)
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library(kableExtra)
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knitr::opts_chunk$set(echo = FALSE, results = "hide", message = FALSE, dev = "cairo_pdf", warning = FALSE)
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knitr::opts_chunk$set(fig.pos = 'H')
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options(knitr.table.format = "latex", knitr.kable.NA = "")
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Sys.setlocale("LC_ALL","English")
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library(here)
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library(foreign)
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library(dplyr)
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library(psych)
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library(ggplot2)
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library(lubridate)
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library(wesanderson)
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library(colortools) # adjacent works
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library(ggthemes) # theme_tufte works
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library(varhandle) # coercing factor to numeric variables
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library(naniar) # for replacing values with missings
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library("Gifi") #Implements categorical principal component analysis
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library(matrixStats) #High-performing functions operating on rows and columns of matrice
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library(cowplot)
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library(tibble)
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library(reshape2) #!new in tool for FMS
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# for tables
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library(knitr)
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library(kableExtra)
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library(formattable) #!new in tool for FMS
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source("Utility functions.R")
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## More functions
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# Response Rate, Non-contact Rate, Refusal Rate, Coop-rate
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r1 <- function(net,gross,i) { (net / (gross - i))*100 }
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# Rate of Ineligibles
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r2 <- function(net,gross){ (net/gross)*100 }
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ESSred <- rgb(.91, .20, .32)
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ESSgreen <- rgb(.14, .62, .51)
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ESSblue <- rgb(0, .25, .48)
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ESSColors <- unique(c(adjacent(ESSred, plot = F), square(ESSred, plot = F)))
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ESSColors <- c(ESSColors, ESSgreen, ESSblue)
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# pizza(ESSColors)
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themeESS <- theme_tufte(base_size = 9, base_family = "Calibri") +
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theme(axis.title = element_text(size = 9, face = "plain"),
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axis.text = element_text(size = 9),
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axis.line.x = element_line(),
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plot.title = element_blank(),
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legend.title = element_blank(),
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legend.text = element_text(size = 9),
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strip.text = element_text(size = 9, face = "bold"),
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legend.position = "none",
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legend.direction = "horizontal",
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legend.box = "vertical",
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legend.spacing = unit(0, "line"),
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legend.key.size = unit(.75, "line"))
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linebreak <- "\\hspace{\\textwidth}"
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# Test data from R9 CF data with Inwer ID (intnum):
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CFR9 <- foreign::read.spss("Data/Test R9/ESS9CFe03.sav",
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use.value.labels = F,
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use.missings = F,
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to.data.frame = T)
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CFR9singlecountry <- CFR9[CFR9$cntry == "DE",] # Assumes the FMS data used is country file. Change country if necessary for test. All countries needs change of full code
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CF <- CFR9singlecountry
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write.table(CFR9singlecountry,"DEMO_DATA_R9/ESS9CFe03_DE.csv", sep = ",", row.names = F)
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#Example Dataset for single country
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CF <- read.csv2("DEMO_DATA_R9/ESS9CFe03_DE.csv", sep = ",", dec=".", stringsAsFactors=F)
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