buildModelCI

Construct Confidence Interval Values

Usage

buildModelCI(model, ...)

# S3 method for default
buildModelCI(
  model,
  outerCI = 2,
  innerCI = 1,
  intercept = TRUE,
  numeric = FALSE,
  sort = c("natural", "magnitude", "alphabetical"),
  predictors = NULL,
  strict = FALSE,
  coefficients = NULL,
  newNames = NULL,
  trans = identity,
  decreasing = TRUE,
  name = NULL,
  interceptName = "(Intercept)",
  ...
)

Arguments

model: A Fitted model such as from lm, glm
...: See Details for information on factors, only and shorten
outerCI: How wide the outer confidence interval should be, normally 2 standard deviations. If 0, then there will be no outer confidence interval.
innerCI: How wide the inner confidence interval should be, normally 1 standard deviation. If 0, then there will be no inner confidence interval.
intercept: logical; Whether the Intercept coefficient should be plotted
numeric: logical; If true and factors has exactly one value, then it is displayed in a horizontal graph with continuous confidence bounds.; not used for now.
sort: Determines the sort order of the coefficients. Possible values are c("natural", "magnitude", "alphabetical")
predictors: A character vector specifying which variables to keep. Each individual variable has to be specified, so individual levels of factors must be specified. We are working on making this easier to implement, but this is the only option for now.
strict: If TRUE then predictors will only be matched to its own coefficients, not its interactions
coefficients: A character vector specifying which factor variables to keep. It will keep all levels and any interactions, even if those are not listed.
newNames: Named character vector of new names for coefficients
trans: A transformation function to apply to the values and confidence intervals. identity by default. Use invlogit for binary regression.
decreasing: logical; Whether the coefficients should be ascending or descending
name: A name for the model, if NULL the call will be used
interceptName: Specifies name of intercept it case it is not the default of "(Intercept").

Value

A data.frame listing coefficients and confidence bands.

Details

Takes a model and builds a data.frame holding the coefficient value and the confidence interval values.

Author

Jared P. Lander

Examples


data(diamonds)
model1 <- lm(price ~ carat + cut, data=diamonds)
coefplot:::buildModelCI(model1)
#>                   Value Coefficient   HighInner    LowInner  HighOuter
#> cut^4          74.59427       cut^4    90.83386    58.35469   107.0734
#> cut.C         367.90995       cut.C   388.12410   347.69579   408.3383
#> cut.Q        -528.59779       cut.Q  -505.46541  -551.73018  -482.3330
#> cut.L        1239.80045       cut.L  1265.90049  1213.70040  1292.0005
#> carat        7871.08213       carat  7885.06176  7857.10251  7899.0414
#> (Intercept) -2701.37602 (Intercept) -2685.94495 -2716.80710 -2670.5139
#>               LowOuter  Model
#> cut^4          42.1151 model1
#> cut.C         327.4816 model1
#> cut.Q        -574.8626 model1
#> cut.L        1187.6004 model1
#> carat        7843.1229 model1
#> (Intercept) -2732.2382 model1
coefplot(model1)



data(diamonds, package='ggplot2')
model1 <- lm(price ~ carat + cut, data=diamonds)
coefplot:::buildModelCI(model1)
#>                   Value Coefficient   HighInner    LowInner  HighOuter
#> cut^4          74.59427       cut^4    90.83386    58.35469   107.0734
#> cut.C         367.90995       cut.C   388.12410   347.69579   408.3383
#> cut.Q        -528.59779       cut.Q  -505.46541  -551.73018  -482.3330
#> cut.L        1239.80045       cut.L  1265.90049  1213.70040  1292.0005
#> carat        7871.08213       carat  7885.06176  7857.10251  7899.0414
#> (Intercept) -2701.37602 (Intercept) -2685.94495 -2716.80710 -2670.5139
#>               LowOuter  Model
#> cut^4          42.1151 model1
#> cut.C         327.4816 model1
#> cut.Q        -574.8626 model1
#> cut.L        1187.6004 model1
#> carat        7843.1229 model1
#> (Intercept) -2732.2382 model1
coefplot(model1)