## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----intro, eval = FALSE------------------------------------------------------ # library(ExPanDaR) # library(gapminder) # # ExPanD(df = gapminder, cs_id = "country", ts_id = "year") ## ----omit_components, eval = FALSE-------------------------------------------- # library(ExPanDaR) # library(gapminder) # data(gapminder) # # ExPanD(df = gapminder, cs_id = "country", ts_id = "year", # components = c(sample_selection = FALSE, missing_values = FALSE)) ## ----select_components, eval = FALSE------------------------------------------ # library(ExPanDaR) # library(gapminder) # data(gapminder) # # ExPanD(df = gapminder, cs_id = "country", ts_id = "year", # components = c(descriptive_table = TRUE, # by_group_violin_graph = TRUE, # scatter_plot = TRUE, # regression = TRUE)) ## ----include_intro, eval = FALSE---------------------------------------------- # library(ExPanDaR) # library(gapminder) # data(gapminder) # # ExPanD(df = gapminder, cs_id = "country", ts_id = "year", # title = "Explore the Preston Curve", # abstract = paste("This interactive display uses 'gapminder' data to", # "let you explore the Preston Curve. Scroll down and enjoy!"), # components = c(descriptive_table = TRUE, # by_group_violin_graph = TRUE, # scatter_plot = TRUE, # regression = TRUE)) ## ----include_df_def, eval = FALSE--------------------------------------------- # library(ExPanDaR) # library(gapminder) # data(gapminder) # # df_def <- data.frame( # var_name = names(gapminder), # var_def = c("Name of the country", # "Continent where country is located", # "Year of data", # "Life expectancy in years at birth", # "Population in million", # "Gross Domestic Product (GDP) per capita"), # type = c("cs_id", "factor", "ts_id", rep("numeric", 3)) # ) # # gapminder$pop <- gapminder$pop / 1e6 # # ExPanD(df = gapminder, # title = "Explore the Preston Curve", # abstract = paste("This interactive display uses 'gapminder' data to", # "let you explore the Preston Curve. Scroll down and enjoy!"), # components = c(descriptive_table = TRUE, # by_group_violin_graph = TRUE, # quantile_trend_graph = TRUE, # scatter_plot = TRUE, # regression = TRUE), # df_def = df_def) ## ----include_dl_clist, eval = FALSE------------------------------------------- # library(ExPanDaR) # library(gapminder) # data(gapminder) # # df_def <- data.frame( # var_name = names(gapminder), # var_def = c("Name of the country", # "Continent where country is located", # "Year of data", # "Life expectancy in years at birth", # "Population in million", # "Gross Domestic Product (GDP) per capita"), # type = c("cs_id", "factor", "ts_id", rep("numeric", 3)) # ) # # gapminder$pop <- gapminder$pop / 1e6 # # clist <- readRDS("my_config.RDS") # # ExPanD(df = gapminder, # title = "Explore the Preston Curve", # abstract = paste("This interactive display uses 'gapminder' data to", # "let you explore the Preston Curve. Scroll down and enjoy!"), # components = c(descriptive_table = TRUE, # by_group_violin_graph = TRUE, # scatter_plot = TRUE, # regression = TRUE), # df_def = df_def, # config_list = clist) ## ----include_manual_clist, eval = FALSE--------------------------------------- # library(ExPanDaR) # library(gapminder) # data(gapminder) # # df_def <- data.frame( # var_name = names(gapminder), # var_def = c("Name of the country", # "Continent where country is located", # "Year of data", # "Life expectancy at birth, in years", # "Population in million", # "Gross Domestic Product (GDP) per capita in US-$, inflation-adjusted"), # type = c("cs_id", "factor", "ts_id", rep("numeric", 3)), # stringsAsFactors = FALSE # ) # # gapminder$pop <- gapminder$pop / 1e6 # # clist <- list( # scatter_x = "gdpPercap", # scatter_y = "lifeExp", # scatter_size = "pop", # scatter_color = "continent", # scatter_loess = TRUE, # scatter_sample = FALSE, # # reg_y = "lifeExp", # reg_x = "gdpPercap", # reg_fe1 = "country", # reg_fe2 = "year", # cluster = "4" # Now this is hard to guess # # 1: none, 2: first FE, 3: second FE, 4: both FE # ) # # ExPanD(df = gapminder, # title = "Explore the Preston Curve", # abstract = paste("This interactive display uses 'gapminder' data to", # "let you explore the Preston Curve. Scroll down and enjoy!"), # components = c(descriptive_table = TRUE, # by_group_violin_graph = TRUE, # scatter_plot = TRUE, # regression = TRUE), # df_def = df_def, # config_list = clist) ## ----include_udvs, eval = FALSE----------------------------------------------- # library(ExPanDaR) # library(gapminder) # data(gapminder) # # df_def <- data.frame( # var_name = names(gapminder), # var_def = c("Name of the country", # "Continent where country is located", # "Year of data", # "Life expectancy in years at birth", # "Population in million", # "Gross Domestic Product (GDP) per capita"), # type = c("cs_id", "factor", "ts_id", rep("numeric", 3)), # stringsAsFactors = FALSE # ) # # gapminder$pop <- gapminder$pop / 1e6 # # clist <- list( # scatter_x = "gdpPercap", # scatter_y = "lifeExp", # scatter_size = "pop", # scatter_color = "continent", # scatter_loess = TRUE, # scatter_sample = FALSE, # # reg_y = "lifeExp", # reg_x = "gdpPercap", # reg_fe1 = "country", # reg_fe2 = "year", # cluster = "4" # No this is hard to guess 1: none, 2: first FE, 3: second FE, 4: both FE # ) # # ExPanD(df = gapminder, # title = "Explore the Preston Curve", # abstract = paste("This interactive display uses 'gapminder' data to", # "let you explore the Preston Curve. Scroll down and enjoy!"), # components = c(descriptive_table = TRUE, # by_group_violin_graph = TRUE, # scatter_plot = TRUE, # udvars = TRUE, # regression = TRUE), # df_def = df_def, # config_list = clist) ## ----include_html, eval = FALSE----------------------------------------------- # library(ExPanDaR) # library(gapminder) # data(gapminder) # # df_def <- data.frame( # var_name = names(gapminder), # var_def = c("Name of the country", # "Continent where country is located", # "Year of data", # "Life expectancy in years at birth", # "Population in million", # "Gross Domestic Product (GDP) per capita"), # type = c("cs_id", "factor", "ts_id", rep("numeric", 3)), # stringsAsFactors = FALSE # ) # # gapminder$pop <- gapminder$pop / 1e6 # # clist <- list( # scatter_x = "gdpPercap", # scatter_y = "lifeExp", # scatter_size = "pop", # scatter_color = "continent", # scatter_loess = TRUE, # scatter_sample = FALSE, # # reg_y = "lifeExp", # reg_x = "gdpPercap", # reg_fe1 = "country", # reg_fe2 = "year", # cluster = "4" # No this is hard to guess 1: none, 2: first FE, 3: second FE, 4: both FE # ) # # html_blocks <- c( # paste('

Variation of life expectancy', # "across regions and income levels

", # '
', # "

 

As you see below, life expectancy varies widely", # "across countries and continents. One potential reason for this", # "variation is the difference in income levels across countries.", # "This association is visualized by the", # "", # "Preston Curve that you also find below.", # "
"), # paste('

Transform variables

', # '
', # "The Preston Curve is far from", # "linear. Maybe you can come up with a transformation", # "of GDP per capita that makes the association", # "a little bit more well behaved?", # "Use the dialog below to define a transformed", # "measure of GDP per capita and assess its association", # "with life expectancy in the scatter plot above.", # "
"), # paste('

Assess Robustness

', # '
', # "You see below that the linear regression coefficient", # "for GDP per capita is negative", # "and signficant in a panel model with country and year", # "fixed effects.", # "Does this also hold when you use a log-transformed version", # "of GDP per capita?", # "
") # ) # # ExPanD(df = gapminder, # title = "Explore the Preston Curve", # abstract = paste("This interactive display uses 'gapminder' data to", # "let you explore the Preston Curve. Scroll down and enjoy!"), # components = c(descriptive_table = TRUE, # html_block = TRUE, # by_group_violin_graph = TRUE, # scatter_plot = TRUE, # html_block = TRUE, # udvars = TRUE, # html_block = TRUE, # regression = TRUE), # df_def = df_def, # config_list = clist, # html_blocks = html_blocks)