bootstrap: Parametric bootstrap

In LMest: Generalized Latent Markov Models

Parametric bootstrap

Description

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

Usage

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

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

Value

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

Author(s)

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

Examples

## Not run: 

# 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)

## End(Not run)

LMest documentation built on Aug. 27, 2023, 5:06 p.m.