summary.DiSSMod {DiSSMod}  R Documentation 
summary
method for a class "DiSSMod"
.
## S3 method for class 'DiSSMod'
summary(object, ...)
## S3 method for class 'summary.DiSSMod'
print(x, digits = max(3, getOption("digits") 
3), ...)
object 
an object of class 
... 
additional control argument is as follows.

x 
an object of class 
digits 
a numeric number of significant digits. 
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
.
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 
level 
a numeric value between 0 and 1 for controlling the significance level of confidence interval.
Initial level is set to 
# 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)