Prerequisites

  • You need to be on BlueSky Statistics 10.1
  • You need very basic Javascript knowledge to create dialogs. Every dialog is a javascript file. There are several sample files that we provide and exercises to get you started.

What Is A Dialog?

  • GUI or a front end for making it easy to perform repeated analysis

Running a logistic model in R involves writing R code that does the following

  • Creates the model
  • Summarize the model
  • Display the coefficients
  • See the analysis of deviance
  • Display pseudo rsquared statistics
  • Display odds ratio
  • See the formula
  • Plot the residuals

There’s a lot of code to write

require(MASS);
require(pscl);
require(equatiomatic)
require(textutils)
#Builds a logistic model 
Logistic1= glm(Survived ~ Class+Sex+Age, weights=, family =binomial(link='logit'), na.action=na.exclude, 
data=titanic.raw)
#Display theoretical model equation and coefficients
#Display theoretical model
reg_formula = equatiomatic::extract_eq(Logistic1, raw_tex = FALSE,
     wrap = TRUE, intercept = "alpha", ital_vars = FALSE) 
BSkyFormat(reg_formula)
#Display coefficients
reg_equation = equatiomatic::extract_eq(Logistic1, use_coefs = TRUE,
     wrap = TRUE,ital_vars = FALSE, coef_digits = BSkyGetDecimalDigitSetting() )
BSkyFormat(reg_equation)
#Summarizing the model
BSky_Logistic = summary(Logistic1)
BSkyFormat(BSky_Logistic, singleTableOutputHeader="Model Summary")
#Analysis of variance
BSky_anova = anova(Logistic1, test="Chisq")
BSkyFormat(as.data.frame(BSky_anova),singleTableOutputHeader="Analysis of Deviance Table")
BSkyFormat(attr(BSky_anova, "heading"))
#McFadden R2
BSkyFormat( pR2(Logistic1) ,singleTableOutputHeader="McFadden R2")
#odds ratio and 95% confidence interval
BSkyFormat(exp(cbind(OR=coef(Logistic1), confint.glm(Logistic1,level=0.95))),singleTableOutputHeader="Odds ratio(OR) and 95% Confidence interval ")

The Output is not pretty

Advantage of a GUI

  • No code to write
    • Eliminate 100’s -1000s lines of code
  • Nicely formatted output
    • Easy copy/paste into Microsoft Office apps
  • Portable output
    • Easy to save and distribute
    • Reproducibility

Sample Dialog

Use a point and click GUI instead of writing R code for popular analysis