causalweight (version 1.1.1)

games: Sales of video games

Description

A dataset containing information on 3956 video games, including sales as well as expert and user ratings.

Usage

games

Format

A data frame with 3956 rows and 9 variables:

name

factor variable providing the name of the video game

genre

factor variable indicating the genre of the game (e.g. Action, Sports...)

platform

factor variable indicating the hardware platform of the game (e.g. PC,...)

esrbrating

factor variable indicating the age recommendation for the game(E is age 6+, T is 13+, M is 17+)

publisher

factor variable indicating the publisher of the game

year

numeric variable indicating the year the video game was released

metascore

numeric variable providing a weighted average rating of the game by professional critics

userscore

numeric variable providing the average user rating of the game

sales

numeric variable indicating the total global sales (in millions) of the game up to the year 2018

References

Wittwer, J. (2020): "Der Erfolg von Videospielen - eine empirische Untersuchung moeglicher Erfolgsfaktoren", BA thesis, University of Fribourg.

Examples

if (FALSE) {
#load data
data(games)
#select non-missing observations
games_nomis=na.omit(games)
#turn year into a factor variable
games_nomis$year=factor(games_nomis$year)
#attach data
attach(games_nomis)
#load library for generating dummies
library(fastDummies)
#generate dummies for genre
dummies=dummy_cols(genre, remove_most_frequent_dummy = TRUE)
#drop original variable
genredummies=dummies[,2:ncol(dummies)]
#make dummies numeric
genredummies=apply(genredummies, 2, function(genredummies) as.numeric(genredummies))
#generate dummies for year
dummies=dummy_cols(year, remove_most_frequent_dummy = TRUE)
#drop original variable
yeardummies=dummies[,2:ncol(dummies)]
#make dummies numeric
yeardummies=apply(yeardummies, 2, function(yeardummies) as.numeric(yeardummies))
# mediation analysis with metascore as treatment, userscore as mediator, sales as outcome
x=cbind(genredummies,yeardummies)
output=medweightcont(y=sales,d=metascore, d0=60, d1=80, m=userscore, x=x, boot=199)
round(output$results,3)
output$ntrimmed}