BIFIE.correl | R Documentation |
Computes correlations and covariances
BIFIE.correl(BIFIEobj, vars, group=NULL, group_values=NULL, se=TRUE) ## S3 method for class 'BIFIE.correl' summary(object,digits=4, ...) ## S3 method for class 'BIFIE.correl' coef(object,type=NULL, ...) ## S3 method for class 'BIFIE.correl' vcov(object,type=NULL, ...)
BIFIEobj |
Object of class |
vars |
Vector of variables for which statistics should be computed |
group |
Optional grouping variable(s) |
group_values |
Optional vector of grouping values. This can be omitted and grouping values will be determined automatically. |
se |
Optional logical indicating whether statistical inference based on replication should be employed. |
object |
Object of class |
digits |
Number of digits for rounding output |
type |
If |
... |
Further arguments to be passed |
A list with following entries
stat.cor |
Data frame with correlation statistics |
stat.cov |
Data frame with covariance statistics |
cor_matrix |
List of estimated correlation matrices |
cov_matrix |
List of estimated covariance matrices |
output |
Extensive output with all replicated statistics |
... |
More values |
stats::cov.wt
,
intsvy::timss.rho
,
intsvy::timss.rho.pv
,
Hmisc::rcorr
,
miceadds::ma.wtd.corNA
############################################################################# # EXAMPLE 1: Imputed TIMSS dataset ############################################################################# data(data.timss1) data(data.timssrep) # create BIFIE.dat object bdat <- BIFIEsurvey::BIFIE.data( data.list=data.timss1, wgt=data.timss1[[1]]$TOTWGT, wgtrep=data.timssrep[, -1 ] ) # Correlations splitted by gender res1 <- BIFIEsurvey::BIFIE.correl( bdat, vars=c("lang", "books", "migrant" ), group="female", group_values=0:1 ) summary(res1) # Correlations splitted by gender: no statistical inference (se=FALSE) res1a <- BIFIEsurvey::BIFIE.correl( bdat, vars=c("lang", "books", "migrant" ), group="female", group_values=0:1, se=FALSE) summary(res1a)
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