BIFIEsurvey (version 1.5-0)

BIFIE.derivedParameters: Statistical Inference for Derived Parameters

Description

This function performs statistical for derived parameters for objects of classes BIFIE.by, BIFIE.correl, BIFIE.crosstab, BIFIE.freq, BIFIE.linreg, BIFIE.logistreg and BIFIE.univar.

Usage

BIFIE.derivedParameters( BIFIE.method , derived.parameters , type=NULL)

## S3 method for class 'BIFIE.derivedParameters':
summary(object,digits=4,...)

## S3 method for class 'BIFIE.derivedParameters':
coef(object,...)

## S3 method for class 'BIFIE.derivedParameters':
vcov(object,...)

Arguments

BIFIE.method

Object of classes BIFIE.by, BIFIE.correl, BIFIE.crosstab,

derived.parameters

List with Rformulas for derived parameters (see Examples for specification)

type

Only applies to BIFIE.correl. In case of type="cov" covariances instead of correlations are used for derived parameters.

object

Object of class BIFIE.derivedParameters

digits

Number of digits for rounding output

...

Further arguments to be passed

Value

• A list with following entries
• stat
  Data frame with statistics
• coef
  Estimates of derived parameters
• vcov
  Covariance matrix of derived parameters
• parnames
  Parameter names
• ...
  More values

Details

The distribution of derived parameters is derived by the direct calculation using original resampled parameters.

See Also

See also BIFIE.waldtest for parameter tests. See car::deltaMethod for the delta method assuming that the multivariate distribution of the parameters is asymptotically normal.

Examples

#############################################################################
# EXAMPLE 1: Imputed TIMSS dataset
#            Inference for correlations and derived parameters
#############################################################################

data(data.timss1)
data(data.timssrep)

# create BIFIE.dat object
bdat <- BIFIE.data( data.list=data.timss1 , wgt=  data.timss1[[1]]$TOTWGT ,
           wgtrep=data.timssrep[, -1 ] )

# compute correlations
res1 <- BIFIE.correl( bdat , vars=c("ASSSCI" , "ASMMAT" , "books" , "migrant" )  )
summary(res1)
res1$parnames
  ##    [1] "ASSSCI_ASSSCI"   "ASSSCI_ASMMAT"   "ASSSCI_books"    "ASSSCI_migrant" 
  ##    [5] "ASMMAT_ASMMAT"   "ASMMAT_books"    "ASMMAT_migrant"  "books_books"    
  ##    [9] "books_migrant"   "migrant_migrant"

# define four derived parameters
derived.parameters <- list( 
        # squared correlation of science and mathematics
        "R2_sci_mat" = ~ 0 + I( 100* ASSSCI_ASMMAT^2  )  ,
        # partial correlation of science and mathematics controlling for books
        "parcorr_sci_mat" = ~ 0 + I( ( ASSSCI_ASMMAT - ASSSCI_books * ASMMAT_books ) /
                            sqrt(( 1 - ASSSCI_books^2 ) * ( 1-ASMMAT_books^2 ) ) ) ,
        # original correlation science and mathematics (already contained in res1)
        "cor_sci_mat" = ~ 0 + I( ASSSCI_ASMMAT ) ,
        # original correlation books and migrant
        "cor_book_migra" = ~ 0 + I( books_migrant )         
        )

# statistical inference for derived parameters
res2 <- BIFIE.derivedParameters( res1 , derived.parameters )
summary(res2)