Graphing mutliple lines (999) on the same xy-plane in r

I have two variables that i want to bootstrap and graph the resulting linear regression line on the same xy plane from each new data set.

I was thinking that i can hold each resulting intercept and slope from the lm() but i dont know how i could graph that information for each resulting pair of information in the same graph. I know that abline() can do one pair but not all of them. Feel free to throw anything at me.

intercept_stuff<-rep(NA,T)

opp_stuff<-rep(NA,T)
N<-1000
for(t in 1:T)
idx <- sample(1:N, size =N, replace=TRUE)
intercept_stuff[t]<- lm(oppose_any~local_topic ,data = facebook[idx,
])$coefficient[1]

opp_stuff[t]<- lm(oppose_any~local_topic ,data = facebook[idx,
])$coefficient[2]



lines()

1 Answer
1

Here is an example of how to do multiple pairs of lines on ggplot with some simulated data. Hopefully this will give you some useful clues:

ggplot

library(reshape2)
library(tibble)

# simulate some data
obs <- c(1:90)
values1 <- rnorm(90,mean=0,sd=1)
values2 <- rnorm(90,mean=5,sd=2)
values3 <- rnorm(90,mean=10,sd=3)
df <- as.tibble(cbind(obs,values1,values2,values3))


It looks like this:

> df
# A tibble: 90 x 4
obs values1 values2 values3
<dbl> <dbl> <dbl> <dbl>
1 1. -0.162 7.47 10.7
2 2. 0.518 5.17 7.61
3 3. 1.52 7.66 4.42
# ... with 80 more rows


Then melt it into long form:

melt

m.df <- melt(df,id="obs",measures=c("values1","values2","values3"))


to look like this:

> m.df
obs variable value
1 1 values1 -0.16228714
2 2 values1 0.51755370
3 3 values1 1.52433685
4 4 values1 -1.82067006
5 5 values1 -1.42180601
...


Then plot many lines (as long as there are groups like the color group here, they will be unique lines):

color

ggplot(m.df,aes(x=obs,y=value,color=variable)) + geom_line()


And here is the plot:

Good luck!

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