CODEWITHSUNDEEP
rggplot2regressionconfidence-interval
Oboeplayingcorgi
Oboeplayingcorgi

Reputation: 21

Plotting Linear Regression Line with Confidence Interval

I am trying to plot how 'Square feet' of a home affects 'Sales Price (in $1000)' of the same. Particularly, I want the coefficient line from Square ft vs. Sales price plotted with a hypothetical grey area around the line with the original datapoints superimposed.

I have tried to complete this a few different ways. One way I have tried is using the function effect_plot from library(jtools). I used the coding I found from https://cran.r-project.org/web/packages/jtools/vignettes/effect_plot.html.

But when I run this function, I don't get a plot, I just get an error: Error in FUN(X[[i]], ...) : object 'Sales Price (in $1000)' not found.

The second way I have attempted is through manually creating a new vector and attempting to plot the confidence interval. My code inspiration is from Plotting a 95% confidence interval for a lm object.

But with this one, I get an error in the conf_interval line: Error in eval(predvars, data, env) : object 'Square feet' not found. I cannot figure out how to correct this error.

And finally, I have tried to use library(ggplot2) to complete the problem with inspiration from https://rpubs.com/aaronsc32/regression-confidence-prediction-intervals.

But each time I run R, it creates a coordinate plane with a single point in the center of the plane; there is no line, no real points, no hypothetical confidence interval. There are no errors and I also cannot figure out the issue with the coding.

library("jtools")
LRA1 <- lm(`Sales Price (in $1000)` ~ `Square feet` + Rooms +
 Bedrooms + Age,data=HomedataSRS) #LRA1 is the regression model
effect_plot(LRA1, pred = 'Square feet', inherit.aes = FALSE,
 plot.points = TRUE) #function should create graph

newSF = seq(min(HomedataSRS$`Square feet`),
            max(HomedataSRS$`Square feet`), by = 0.05)
conf_interval <- predict(LRA1, newdata=data.frame(x=newSF),
                 interval="confidence",level = 0.95)
plot(HomedataSRS$`Square feet`, HomedataSRS$`Sales Price (in $1000)`,
     xlab="Square feet", ylab="Sales Price(in $1000)",     
     main="Regression")
abline(LRA1, col="lightblue")
matlines(newSF, conf_interval[,2:3], col = "blue", lty=2)

library(ggplot2)
SFHT <- HomedataSRS %>% select(1:2) 
#This is to select the 2 variables I'm working with
ggplot(SFHT, aes(x='Square feet', inherit.aes = FALSE, 
       y='Sales Price (in $1000)')) +
       geom_point(color='#2980B9', size = 4) +
       geom_smooth(method=lm, color='#2C3E50')

Data: I take an n=35 random sample of this data with set.seed(1)

Upvotes: 2

Views: 2008

Answers (1)

Wil
Wil

Reputation: 3188

arguments to aes() should not be quoted. Try

ggplot(SFHT, aes(x = `Square feet`, y = `Sales Price (in $1000)`)) +
   geom_point(color='#2980B9', size = 4) +
   geom_smooth(method=lm, color='#2C3E50')

alternatively, you could use the new aes_string() function:

ggplot(SFHT, aes_string(x='Square feet',y='Sales Price (in $1000)')) +
   geom_point(color='#2980B9', size = 4) +
   geom_smooth(method=lm, color='#2C3E50')

more info is available on the package site: https://ggplot2.tidyverse.org/reference/aes_.html

Upvotes: 1

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