3.9 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:

  • MODELNAME <- lm(Y~X, data=DATASETNAME)

    • Probably the most frequently used command in R.

    • Here it is used to fit the reference-coded One-Way ANOVA model with Y as the response variable and X as the grouping variable, storing the estimated model object in MODELNAME. Remember that X should be defined as a factor variable.

  • MODELNAME <- lm(Y~X-1, data=DATASETNAME)

    • Fits the cell means version of the One-Way ANOVA model.

  • summary(MODELNAME)

    • Generates model summary information including the estimated model coefficients, SEs, t-tests, and p-values.

  • anova(MODELNAME)

    • Generates the ANOVA table but must only be run on the reference-coded version of the model.

    • Results are incorrect if run on the cell-means model since the reduced model under the null is that the mean of all the observations is 0!

  • pf(FSTATISTIC, df1=NUMDF, df2=DENOMDF, lower.tail=F)

    • Finds the p-value for an observed \(F\)-statistic with NUMDF and DENOMDF degrees of freedom.

  • par(mfrow=c(2,2)); plot(MODELNAME)

    • Generates four diagnostic plots including the Residuals vs Fitted and Normal Q-Q plot.

  • plot(allEffects(MODELNAME))

    • Requires the effects package be loaded.

    • Plots the estimated model component.

  • Tm2 <- glht(MODELNAME, linfct=mcp(X=“Tukey”)); confint(Tm2); plot(Tm2); summary(Tm2); cld(Tm2)

    • Requires the multcomp package to be installed and loaded.

    • Can only be run on the reference-coded version of the model.

    • Generates the text output and plot for Tukey’s HSD as well as the compact letter display information.