plotCI.yhat: Plot CIs from yhat

In yhat: Interpreting Regression Effects

Plot CIs from yhat

Description

This function plots CIs that have been produced from /codebooteval.yhat.

Usage

  plotCI.yhat(sampStat, upperCI, lowerCI, pid=1:ncol(sampStat), nr=2, nc=2)

Arguments

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)

Details

This function plots CIs that have been produced from /codebooteval.yhat.

Value

This returns a plot of CIs that have been produced from /codebooteval.yhat.

Author(s)

Kim Nimon <[e-mail]>

References

Nimon, K., & Oswald, F. L. (2013). Understanding the results of multiple linear regression: Beyond standardized regression coefficients. Organizational Research Methods, 16, 650-674.

See Also

lm calc.yhat boot booteval.yhat

Examples

  ## 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)
     }

yhat documentation built on Oct. 11, 2023, 1:08 a.m.