LMest (version 3.1.2)

lmestFormula: Formulas for LMest functions

Description

Bulding formulas for lmest, lmestCont, lmestMixed, and lmestMc.

Usage

lmestFormula(data,
              response, manifest = NULL,
              LatentInitial = NULL, LatentTransition = NULL,
              AddInterceptManifest = FALSE,
              AddInterceptInitial = TRUE,
              AddInterceptTransition = TRUE, responseStart = TRUE,
              manifestStart = TRUE, LatentInitialStart = TRUE,
              LatentTransitionStart = TRUE)

Value

Returns a list with responsesFormula and latentFormula objects.

Arguments

data

a data.frame or a matrix of data

response

a numeric or character vector indicating the column indices or the names for the response variables

manifest

a numeric or character vector indicating the column indices or the names for the covariates affecting the measurement model

LatentInitial

a numeric or character vector indicating the column indices or the names for the covariates affecting the initial probabilities

LatentTransition

a numeric or character vector indicating the column indices or the names for the covariates affecting the transition probabilities

AddInterceptManifest

a logical value indicating whether the intercept is added to the covariates affecting the measurement model

AddInterceptInitial

a logical value indicating whether the intercept is added to covariates affecting the initial probabilities

AddInterceptTransition

a logical value indicating whether the intercept is added to covariates affecting the transition probabilities

responseStart

a logical value indicating whether the response variables names start with response argument

manifestStart

a logical value indicating whether the covariates names start with manifest argument

LatentInitialStart

a logical value indicating whether the covariates names start with LatentInitial argument

LatentTransitionStart

a logical value indicating whether the covariates names start with LatentTransition argument

Author

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

Details

Generates formulas for responsesFormula and latentFormula to use in lmest, lmestCont, lmestMixed, and lmestMc.

Examples

data(data_SRHS_long)
names(data_SRHS_long)

# Formula with response srhs and covariates for both initail and transition: 
# gender,race,educational,age.

## LM model with covariates on the latent model
# and with intercepts on the initial and transition probabilities

fm <- lmestFormula(data = data_SRHS_long,
                   response = "srhs",
                   LatentInitial = 3:6, LatentTransition = 3:6)
fm

## LM model with covariates on the latent model
# and without intercepts on the initial and transition probabilities

fm <- lmestFormula(data = data_SRHS_long,
                   response = "srhs",
                   LatentInitial = 3:6, LatentTransition = 3:6,
                   AddInterceptInitial = FALSE,AddInterceptTransition = FALSE)
fm

######

data(data_criminal_sim)
str(data_criminal_sim)

# Formula with only the responses from y1 to y10

fm <- lmestFormula(data = data_criminal_sim,response = "y")$responsesFormula
fm

# Formula with only the responses from y1 to y10 and intercept for manifest

fm <- lmestFormula(data = data_criminal_sim,
                   response = "y",AddInterceptManifest = TRUE)$responsesFormula
fm


## LM model for continous responses

data(data_long_cont)
names(data_long_cont)

# Formula with response Y1, Y2, no covariate for manifest,
# X1 covariates for initail and X2 covariate for transition

fm <- lmestFormula(data = data_long_cont,
                   response = c("Y"),
                   LatentInitial = "X",
                   LatentTransition = "X2")
fm

## Wrong model specification since two variable start with X.
# Check the starts arguments. 

# For the right model:

fm <- lmestFormula(data = data_long_cont,
                   response = c("Y"),
                   LatentInitial = "X1",LatentTransition = "X2")
fm

## or

fm <- lmestFormula(data = data_long_cont,
                   response = c("Y"),
                   LatentInitial = 6,LatentTransition = "X2",
                   LatentInitialStart = FALSE)
fm

if (FALSE) {

data(data_criminal_sim)
data_criminal_sim <- data.frame(data_criminal_sim)

# Mixed LM model for females

responsesFormula <- lmestFormula(data = data_criminal_sim,
                                 response = "y")$responsesFormula

out <- lmest(responsesFormula = responsesFormula,
             index = c("id","time"),
             data = data_criminal_sim,
             k = 2)
}