Create a factor-level variable and regress deportations as a function of it: \(\hat{D}=\beta_0 + \beta_1Party\)
1=Democrat; 0=Republican
#Create factor-level variable
remove.1$PartyofPres<-factor(remove.1$Party,
levels=c(0,1),
labels=c("Republican", "Democrat"))
summary(remove.1$PartyofPres)
## Republican Democrat
## 40 35
#"Regress" deportations "on" decade
reg1<-lm(Deportations~PartyofPres, data=remove.1)
summary(reg1)
##
## Call:
## lm(formula = Deportations ~ PartyofPres, data = remove.1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -118080 -87243 -71318 82297 306491
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 94800 21372 4.436 0.0000319 ***
## PartyofPresDemocrat 31043 31286 0.992 0.324
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 135200 on 73 degrees of freedom
## Multiple R-squared: 0.01331, Adjusted R-squared: -0.0002093
## F-statistic: 0.9845 on 1 and 73 DF, p-value: 0.3244
plot_model(reg1, type = "pred", terms = c("PartyofPres"), ci.lvl = .95,
title="Use of deportations by Republican and Democratic Presidents \nshows no differences, 1948-1922", axis.title=c("Party", "Number of removals"), colors=c("coral2")) +
geom_line(color=c("coral2"), size=1) +
theme_classic()
plot_model : invokes sjPlot and tells R to plot a regression object.
reg1 : It is the name of the regression object you want to plot.
type=“pred” : Informs plot_model to plot predicted values from regression function
terms=c(“PartyofPres) : Corresponds to the name of the independent variable(s) used in the regression model. It is case-sensitive and must be identical to what you specified in lm .
ci.lvl: .95 : Specifies confidence level (here we specify the 95% level)
title=“Use of deportations by Republican and Democratic Presidents no differences, 1948-1922”, axis.title=c(“Party”, “Number of removals”) : Gives main title, and axis titles (x-axis first, y-axis second).
colors=c(“coral2”)) : Specifies color of objects in plot_model .
geom_line(color=c(“coral2”), size=1) : Adding a line to connect the plot points (used here to show differences)
theme_classic() : This controls the appearance of the overall plot. There are many themes. Google ggplot2 themes to see them.