summary.DiSSMod {DiSSMod} R Documentation

## Summarizing Discrete Sample Selection Model Fits

### Description

summary method for a class "DiSSMod".

### Usage

## S3 method for class 'DiSSMod'
summary(object, ...)

## S3 method for class 'summary.DiSSMod'
print(x, digits = max(3, getOption("digits") -
3), ...)


### Arguments

 object an object of class "DiSSMod" made by the function DiSSMod. ... additional control argument is as follows. level: an option for controlling the significance level of confidence interval. It has to be given in probability between 0 and 1. Initial level is set to 1 - \alpha = 0.95. x an object of class "summary.DiSSMod". digits a numeric number of significant digits.

### Details

If standard equals TRUE, summary also additionally returns summary statistics of standardized results. Otherwise, it just returns summary statistics as similar statistics as the generic function summary.

### Value

The function summary.DiSSMod returns a list of summary statistics of the fitted discrete sample selection model given in object.

The components, which are not duplicated from the object, are as follows:

 z.value_response Z statistics (normal distribution) for coefficients of response equation. z.value_selection Z statistics (normal distribution) for coefficients of selection equation. CI_alpha confidence interval of the parameter alpha. level a numeric value between 0 and 1 for controlling the significance level of confidence interval. Initial level is set to 1 - \alpha = 0.95.

See also DiSSMod and summary.

### Examples

# example continued from DiSSMod
set.seed(45)
data(DoctorRWM, package = "DiSSMod")
n0 <- 600
set.n0 <- sample(1:nrow(DoctorRWM), n0)
reduce_DoctorRWM <- DoctorRWM[set.n0,]
result0 <- DiSSMod(response = as.numeric(DOCVIS > 0) ~ AGE + INCOME_SCALE + HHKIDS + EDUC + MARRIED,
selection = PUBLIC ~ AGE + EDUC + FEMALE,
data = reduce_DoctorRWM, resp.dist="bernoulli", select.dist = "normal",
alpha = seq(-5.5, -0.5, length.out = 21), standard = TRUE)

summary(result0, level = 0.90)

data(CreditMDR, package = "DiSSMod")
n1 <- 600
set.n1 <- sample(1:nrow(CreditMDR), n1)
reduce_CreditMDR <- CreditMDR[set.n1,]
result1 <- DiSSMod(response = MAJORDRG ~ AGE + INCOME + EXP_INC,
selection = CARDHLDR ~ AGE + INCOME + OWNRENT + ADEPCNT + SELFEMPL,
data = reduce_CreditMDR, resp.dist="poi", select.dist = "logis",
alpha = seq(-0.3, 0.3,length.out = 21), standard = FALSE, verbose = 1)

summary(result1)



[Package DiSSMod version 1.0.0 Index]