2.12: Summary of important R code

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2.12 Summary of important R code

The main components of R code used in this chapter follow with components to modify in lighter and/or ALL CAPS text, remembering that any R packages mentioned need to be installed and loaded for this code to have a chance of working:

summary(DATASETNAME)
- Provides numerical summaries of all variables in the data set.
summary(lm(Y ~ X, data = DATASETNAME))
- Provides estimate, SE, test statistic, and p-value for difference in second row of coefficient table.
confint(lm(Y ~ X, data = DATASETNAME), level = 0.95)
- Provides 95% confidence interval for difference in second row of output.
2*pt(abs(Tobs), df = DF, lower.tail = F)
- Finds the two-sided test p-value for an observed 2-sample t-test statistic of Tobs.
hist(DATASETNAME$Y)
- Makes a histogram of a variable named Y from the data set of interest.
boxplot(Y ~ X, data = DATASETNAME)
- Makes a boxplot of a variable named Y for groups in X from the data set.
pirateplot(Y ~ X, data = DATASETNAME, inf.method = “ci”, inf.disp = “line”)
- Requires the yarrr package is loaded.
- Makes a pirate-plot of a variable named Y for groups in X from the data set with estimated means and 95% confidence intervals for each group.
- Add theme = 2 if the confidence intervals extend outside the density curves and you can’t see how far they extend.
mean(Y ~ X, data = DATASETNAME); sd(Y ~ X, data = DATASETNAME)
- This usage of mean and sd requires the mosaic package.
- Provides the mean and sd of responses of Y for each group described in X.
favstats(Y ~ X, data = DATASETNAME)
- Provides numerical summaries of Y by groups described in X.
Tobs <- coef(lm(Y ~ X, data = DATASETNAME))[2]; Tobs
B <- 1000
Tstar <- matrix(NA, nrow = B)
for (b in (1:B)){
lmP <- lm(Y ~ shuffle(X), data = DATASETNAME)
Tstar[b] <- coef(lmP)[2]
}
- Code to run a for loop to generate 1000 permuted versions of the test statistic using the shuffle function and keep track of the results in Tstar
pdata(Tstar, abs(Tobs), lower.tail = F)
- Finds the proportion of the permuted test statistics in Tstar that are less than -|Tobs| or greater than |Tobs|, useful for finding the two-sided test p-value.

Tobs <- coef(lm(Y ~ X, data = DATASETNAME))[2]; Tobs
B <- 1000
Tstar <- matrix(NA, nrow = B)
for (b in (1:B)){
lmP <- lm(Y ~ X, data = resample(DATASETNAME))
Tstar[b] <- coef(lmP)[2]
}
- Code to run a for loop to generate 1000 bootstrapped versions of the data set using the resample function and keep track of the results of the statistic in Tstar.

qdata(Tstar, c(0.025, 0.975))
- Provides the values that delineate the middle 95% of the results in the bootstrap distribution (Tstar).