LMest (version 3.1.2)

bootstrap: Parametric bootstrap

Description

Function that performs bootstrap parametric resampling to compute standard errors for the parameter estimates.

Usage

bootstrap(est, ...)
# S3 method for LMbasic
bootstrap(est, n = 1000, B = 100, seed = NULL, ...)
# S3 method for LMbasiccont
bootstrap(est, n = 1000, B=100, seed = NULL, ...)
# S3 method for LMlatent
bootstrap(est, B = 100, seed = NULL, ...)
# S3 method for LMlatentcont
bootstrap(est, B = 100, seed = NULL, ...)

Value

Average of bootstrap estimates and standard errors for the model parameters in est object.

Arguments

est

an object obtained from a call to lmest and lmestCont

n

sample size

B

number of bootstrap samples

seed

an integer value with the random number generator state

...

further arguments

Author

Francesco Bartolucci, Silvia Pandolfi, Fulvia Pennoni, Alessio Farcomeni, Alessio Serafini

Examples

if (FALSE) {

# LM model for categorical responses with covariates on the latent model

data("data_SRHS_long")
SRHS <- data_SRHS_long[1:2400,]

# Categories rescaled to vary from 0 (“poor”) to 4 (“excellent”)

SRHS$srhs <- 5 - SRHS$srhs

out1 <- lmest(responsesFormula = srhs ~ NULL,
              index = c("id","t"),
              data = SRHS,
              k = 3,
              tol = 1e-8,
              start = 1,
              modBasic = 1,
              out_se = TRUE,
              seed = 123)

boot1 <- bootstrap(out1)

out2 <- lmest(responsesFormula = srhs ~ NULL,
              latentFormula =  ~
              I(gender - 1) +
              I( 0 + (race == 2) + (race == 3)) +
              I(0 + (education == 4)) +
              I(0 + (education == 5)) +
              I(age - 50) + I((age-50)^2/100),
              index = c("id","t"),
              data = SRHS,
              k = 2,
              paramLatent = "multilogit",
              start = 0)

boot2 <- bootstrap(out2)

# LM model for continous responses without covariates 

data(data_long_cont)

out3 <- lmestCont(responsesFormula = Y1 + Y2 + Y3 ~ NULL,
                  index = c("id", "time"),
                  data = data_long_cont,
                  k =3,
                  modBasic=1,
                  tol=10^-5)

boot3 <- bootstrap(out3)

# LM model for continous responses with covariates 

out4 <- lmestCont(responsesFormula = Y1 + Y2 + Y3 ~ NULL,
                  latentFormula = ~ X1 + X2,
                  index = c("id", "time"),
                  data = data_long_cont,
                  k = 3,
                  output=TRUE)
                  
boot4 <- bootstrap(out4)
}