predicts {glm.predict}

predicted values and discrete change

Description

The function calculates the predicted values and the difference of a range of cases with the confidence interval. It can be used for any glm, polr or multinom model.

Usage

predicts(model, values, position = NULL, sim.count = 1000, conf.int = 0.95, 
  sigma = NULL, set.seed = NULL, doPar = FALSE,
  type = c("any", "simulation", "bootstrap"))

Arguments

model

the model-Object generated with glm(), glm.nb(), polr(), multinom(), mlogit() or tobit()

values

The values of cases as character in the order how they appear in the summary(model) Estimate. The values must be in the following way: "value1;value2;value3;...". Each one of the values can be one of the following:

• "all": takes all unique values of that variable

• "mean": takes the mean of that variable (can only be used when the variable is numeric)

• "median": takes the median of that variable (assumes for factors that they are correctly ordered)

• "mode": takes the mode of that variable

• "Q4": takes the quartiles (0,0.25,0.5,0.75,1) of that variable (other number for other quantiles)

• "min": takes the minimum of that variable

• "max": takes the maximum of that variable

• from-to,by: takes all values from "from" to "to" with the distance "by" (for example: "160-180,5" –> 160,165,170,175,180)

• from-to: same as from-to,by with by=1 (for example: "2-8" –> 2,3,4,5,6,7,8); also works for factors and takes the given levels form their position

• value1,value2,value3,...: takes the given values (for example: "160,180" –> 160,180); also works for factors and takes the given levels form their position

• value1: takes the given value (for example: "5.34" –> 5.34); also works for factors and takes the given level form its position

• log(from-to,by): takes the log of all values from "from" to "to" with the distance "by" (for example: "160-180,5" –> 160,165,170,175,180)

• log(from-to): same as log(from-to,by) with by=1 (for example: "2-8" –> 2,3,4,5,6,7,8)

• log(value1,value2,value3,...): takes the log of the given values (for example: "160,180" –> 160,180)

• log(value1): takes the log of the given value (for example: "5.34" –> 5.34)

• "F": takes all values of a factor/character

• "F(1,4,7)": takes the first, fourth and seventh level of a factor/character

• "F(2)": takes the second level of a factor/character

position

OPTIONAL which variable should be taken for the discrete change, the variable must have at least two values. default: only predicted probabilities

sim.count

OPTIONAL numbers of simulations to be done by the function. default: 1000

conf.int

OPTIONAL the confidence interval used by the function. default: 0.95

sigma

OPTIONAL the variance-covariance matrix, can be changed when having for example robust or clustered vcov. default: vcov(model)

set.seed

OPTIONAL set a seed for the random number generator

doPar

OPTIONAL if the code should run parallel if more than 2 cores are detected

type

OPTIONAL choose between simulation and bootstrap, "any" chooses between those two according to the number of cases (bootstrap if n < 500)

Details

The function makes a simulation for the all combination of cases and compares them to each other.

Value

The output is a data.frame with the predicted values and discrete changes.

Author(s)

Benjamin Schlegel, [e-mail]

Examples

## Not run: 
model1 = glm(Sex ~ Height + Smoke + Pulse, data=MASS::survey, family=binomial(link=logit))
summary(model1)
# comparing person with hight 150 to 160, 160 to 170, 170 to 180, 180 to 190 
# with all combination of(non-)smokers and a median of pulse 
predicts(model1, "150-190,10;F;median", position = 1, doPar = FALSE)

## End(Not run)