R/display2.R
regress.display2.Rd
regress.display function for reactive data
regress.display2( regress.model, alpha = 0.05, crude = FALSE, crude.p.value = FALSE, decimal = 2, simplified = FALSE )
regress.model | lm object |
---|---|
alpha | alpha, Default: 0.05 |
crude | crude, Default: FALSE |
crude.p.value | crude.p.value, Default: FALSE |
decimal | decimal, Default: 2 |
simplified | simplified, Default: FALSE |
regress table
regress.display function for reactive data
model1 <- glm(mpg ~ cyl + disp + vs, data = mtcars) regress.display2(model1, crude = TRUE, crude.p.value = TRUE, decimal = 3)#> Linear regression predicting mpg #> #> crude coeff.(95%CI) crude P value adj. coeff.(95%CI) #> cyl (cont. var.) -2.876 (-3.534,-2.217) < 0.001 -1.75 (-3.537,0.037) #> #> disp (cont. var.) -0.041 (-0.051,-0.032) < 0.001 -0.02 (-0.042,0.001) #> #> vs: 1 vs 0 7.94 (4.607,11.274) < 0.001 -0.634 (-4.517,3.25) #> #> P(t-test) P(F-test) #> cyl (cont. var.) 0.0545 < 0.001 #> #> disp (cont. var.) 0.0624 0.0581 #> #> vs: 1 vs 0 0.7407 0.7407 #> #> Log-likelihood = -79.5091 #> No. of observations = 32 #> AIC value = 169.01821 #>