Plot CIs from yhat
This function plots CIs that have been produced from /codebooteval.yhat.
plotCI.yhat(sampStat, upperCI, lowerCI, pid=1:ncol(sampStat), nr=2, nc=2)
sampStat |
Set of sample statistics |
upperCI |
Set of upper CIs |
lowerCI |
Set of lower CIs |
pid |
Which set of Metrics to plot (default to all) |
nr |
Number of rows (default = 2) |
nc |
Number of columns(default = 2) |
This function plots CIs that have been produced from /codebooteval.yhat.
This returns a plot of CIs that have been produced from /codebooteval.yhat.
Kim Nimon <kim.nimon@gmail.com>
Nimon, K., & Oswald, F. L. (2013). Understanding the results of multiple linear regression: Beyond standardized regression coefficients. Organizational Research Methods, 16, 650-674.
## Bootstrap regression results predicting paragraph
## comprehension based on three verbal tests: general info,
## sentence comprehension, & word classification
## Use HS dataset in MBESS
if (require("MBESS")){
data(HS)
## Regression
lm.out<-lm(t6_paragraph_comprehension~
t5_general_information+t7_sentence+t8_word_classification,data=HS)
## Calculate regression metrics
regrOut<-calc.yhat(lm.out)
## Bootstrap results
require ("boot")
boot.out<-boot(HS,boot.yhat,100,lmOut=lm.out,regrout0=regrOut)
## Evaluate bootstrap results
result<-booteval.yhat(regrOut,boot.out,bty="perc")
## Plot results
## plotCI.yhat(regrOut$PredictorMetrics[-nrow(regrOut$PredictorMetrics),],
## result$upperCIpm,result$lowerCIpm, pid=which(colnames(regrOut$PredictorMetrics)
## %in% c("Beta","rs","CD:0","CD:1","CD:2","GenDom","Pratt","RLW") == TRUE),nr=3,nc=3)
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.