Chapter 14 Create Data Set
This chapter describes the process of loading the full NCP data set and from that creating a sample data set with the relevant variables for the Good Loser conjoint experiment.
14.1 Load packages or install them if not already installed
if(!require("ggplot2")){install.packages("ggplot2"); library(ggplot2)}
if(!require("tidyverse")){install.packages("tidyverse"); library(tidyverse)}
if(!require("haven")){install.packages("haven"); library(haven)}
if(!require("knitr")){install.packages("knitr"); library(knitr)}
if(!require("readxl")){install.packages("readxl"); library(readxl)}
if(!require("Hmisc")){install.packages("Hmisc"); library(Hmisc)}
if(!require("likert")){install.packages("likert"); library(likert)}
if(!require("naniar")){install.packages("naniar"); library(naniar)}
if(!require("ggthemes")){install.packages("ggthemes"); library(ggthemes)}
knitr::opts_chunk$set(echo = FALSE, knitr.kable.NA = "", cache = FALSE, warning = FALSE, message = FALSE, error = TRUE, echo = FALSE)
14.2 Load raw NCP data
Select variables of interest for the good loser experiment, recode, and create new data set in .sav and .csv formats
d_1 <- read_sav("C:\\Users/Sveinung/OneDrive/NORCE 2018-/goodloser/Conjoint/Bookdown-goodloser/Data/Norwegian Citizen Panel - wave 1-13 - EN.sav")
d_1 <- d_1 %>%
select(responseid, #Select variables of interest for the good loser experiment
r13pad1,
r13pad2,
r13pad3,
r13pad4,
r13pad5_avsender,
r13pad5_sak,
r13pad5_utfall,
r13pad5_vinner,
r13pad5_vinnermargin,
r13pad6_ran,
r13pad6a,
r13pad6b,
r13pad7a,
r13pad7b,
r13pad8a,
r13pad8b
)
14.3 Load Time tracker data
The time tracker data set is a separate data set that provides information about how long the respondents spent on answering the three post measure questions in the Good loser experiment.
d_2 <- read_xlsx("C:\\Users/Sveinung/OneDrive/NORCE 2018-/goodloser/Conjoint/Bookdown-goodloser/Data/TimeTracker - runde 13.xlsx")
d_2 <- d_2 %>%
select(responseid = responseID,
timeTracker2_R13PAD6A,
timeTracker2_R13PAD6B
) %>%
gather(Scale_time, time, timeTracker2_R13PAD6A:timeTracker2_R13PAD6B) %>%
filter(!is.na(time))
14.4 Merge data sets
d <- left_join(d_1, d_2, by= "responseid") %>%
filter(!is.na(time))
d %>% write_sav("Data/Goodloser-exp3.sav") %>% #Create data file, .sav format
write.csv("Data/Goodloser-exp3.csv") #Create data file, .csv format