svyjdivdec na.rm = FALSE related error for replication designs

[ajdamico]

# load libraries
library( survey )
library( convey )
library( laeken )

# collect and format data
data( eusilc )
names( eusilc ) <- tolower( names( eusilc ) )

# set up survey design objects
des_eusilc <- svydesign( ids = ~rb030 , strata = ~db040 , weights = ~rb050 , data = eusilc )
des_eusilc_rep <-as.svrepdesign( des_eusilc , type= "bootstrap" , replicates = 50 )

# prepare for convey
des_eusilc <- convey_prep( des_eusilc )
des_eusilc_rep <- convey_prep( des_eusilc_rep )

# filter positive
des_eusilc <- subset( des_eusilc , py010n > 0 | is.na( py010n ) )
des_eusilc_rep <- subset( des_eusilc_rep , py010n > 0 | is.na( py010n ) )

# all three functions work fine with na.rm = TRUE
svygpg( ~ py010n , sex = ~ rb090 , des_eusilc_rep , na.rm = TRUE )
svyjdivdec( ~ py010n , ~ rb090 , des_eusilc_rep , na.rm = TRUE )
svygeidec( ~ py010n , ~ rb090 , des_eusilc_rep , na.rm = TRUE )

# removing na.rm = TRUE #

# all three behave the same linearized
svygpg( ~ py010n , sex = ~ rb090 , des_eusilc )
svyjdivdec( ~ py010n , ~ rb090 , des_eusilc )
svygeidec( ~ py010n , ~ rb090 , des_eusilc )

# svyjdivdec gives an error, even though similar functions do not
# and linearized svyjdivdec also does not
svygpg( ~ py010n , sex = ~ rb090 , des_eusilc_rep )
svyjdivdec( ~ py010n , ~ rb090 , des_eusilc_rep )
svygeidec( ~ py010n , ~ rb090 , des_eusilc_rep )

# there are non-missing values in all groups of py010n
with( des_eusilc_rep$variables , table( is.na( py010n ) , rb090 ) )

[ajdamico]

whoops sorry this is fixed