svyPVlevel | R Documentation |
This function categorizes the plausible values into specific user defined levels, to estimate the proportion of population totals within this levels.
svyPVlevel(by, svydat, pvs, CATDEF, levlab = NA, right = TRUE, colN = FALSE)
by |
A formula statement is expected which splits the data into several subsets. |
svydat |
A survey design ( |
pvs |
A character vector which includes the colnames of the plausible
values. These variables must be part of the survey design comitted as
|
CATDEF |
A numeric vector which contains the cut points with which the
plausible values are categorized. The input follows the same notation as the
break argument in the |
levlab |
A character vector which contains the levels labels. Default
is NA – which means that the labels will be |
right |
Corresponds to the right argument in the |
colN |
If TRUE the colnames will equal the grouping variable names from the by statement. If FALSE, which is the default, the names will be Group1 up to Group k. |
All variables, including the subsetting ones defined with by
, must be
part of the survey design object.
Missing values are deleted listwise.
Note that '.' is not allowed as part of the level string of a by
variable. For example c("1.thing","2.thing") is not allowed and will cause a
error message.
The function returns a data.frame with the following columns
Group1..k |
The first k-1 columns show the different levels of the k-1
subsetting groups, provided with |
Number.of.cases |
Shows the unweighted number of cases (NA's excluded) within each group. |
Sum.of.weights |
Shows the sum of weights (NA's excluded) within each group. |
Proportion |
Contains the estimate of the conditional proportion of persons on each level given the categories of the first k-1 groups. |
Proportion.SE |
Contains the SE of the proportion estimate. |
Manuel Reif
Lumley, T. (2010). Complex Surveys. Hoboken, NJ: Wiley.
Saerndal, C.-E. & Swensson, B. & Wretman, J. (1992). Model Assisted Survey Sampling. New York: Springer.
Chaudhuri, A. & Stenger, H. (2005). Survey Sampling. Theory and Methods. Boka Raton, FL: Chapman & Hall/CRC.
svyPVbenchmark
data(svy_example1)
erg_l <- svyPVlevel(by = ~ sex, svydat=svy.exrep,
pvs=c("plaus1","plaus2","plaus3"), CATDEF=c(0,310,322,400))
erg_l
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.