7.9: Summary of important R code
- Page ID
- 33288
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)The main components of the R code used in this chapter follow with the components to modify in lighter and/or ALL CAPS text where y
is a response variable, x
is an explanatory variable, and the data are in DATASETNAME
.
- DATASETNAME %>% ggplot(mapping = aes(x = x, y = y)) + geom_point() + geom_smooth(method = “lm”)
- Provides a scatter plot with a regression line.
- Add + geom_smooth() to add a smoothing line to help detect nonlinear relationships.
- MODELNAME
<-
lm(y ~ x, data = DATASETNAME)- Estimates a regression model using least squares.
- summary(MODELNAME)
- Provides parameter estimates and R-squared (used heavily in Chapter 8 as well).
- par(mfrow = c(2, 2)); plot(MODELNAME)
- Provides four regression diagnostic plots in one plot.
- confint(MODELNAME, level = 0.95)
- Provides 95% confidence intervals for the regression model coefficients.
- Change
level
if you want other confidence levels.
- plot(allEffects(MODELNAME))
- Requires the
effects
package. - Provides a term-plot of the estimated regression line with 95% confidence interval for the mean.
- Requires the
- DATASETNAME
<-
DATASETNAME %>% mutate(log.y = log(y)- Creates a transformed variable called log.y – change this to be more specific to your “\(y\)” or “\(x\)”.
- predict(MODELNAME, se.fit = T)
- Provides fitted values for all observed \(x\text{'s}\) with SEs for the mean.
- predict(MODELNAME, newdata = tibble(x = XNEW), interval = “confidence”)
- Provides fitted value for a specific \(x\) (XNEW) with CI for the mean. Replace
x
with name of explanatory variable.
- Provides fitted value for a specific \(x\) (XNEW) with CI for the mean. Replace
- predict(MODELNAME, newdata = tibble(x = XNEW), interval = “prediction”)
- Provides fitted value for a specific \(x\) (XNEW) with PI for a new observation. Replace
x
with name of explanatory variable.
- Provides fitted value for a specific \(x\) (XNEW) with PI for a new observation. Replace
- qt(0.975, df = n - 2)
- Gets the \(t^*\) multiplier for making a 95% confidence or prediction interval with \(n-2\) replaced by the sample size – 2.