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fixed bug with fpc calculation
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Johannes Gussenbauer - QM committed Apr 10, 2019
1 parent 5adb6b7 commit 0824834
Showing 1 changed file with 3 additions and 13 deletions.
16 changes: 3 additions & 13 deletions R/draw.bootstrap.R
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Original file line number Diff line number Diff line change
Expand Up @@ -295,7 +295,7 @@ draw.bootstrap <- function(

# check totals
# if clusters are specified the finite population correction factors must
# be user specified (at least for now)
# be user specified
# check input for totals
# if no totals are specified then leave them NULL
if (is.null(totals)) {
Expand All @@ -305,19 +305,9 @@ draw.bootstrap <- function(
totals <- "fpc"
fpc.strata <- strata[!strata %in% c("I", "1")] # nolint
dt.eval("dat[,fpc:=sum(", weights, "[!duplicated(",
hid, ")]),by=c(fpc.strata)]")
hid, ")]),by=c(fpc.strata,period)]")
} else {
# else leave totals NULL
# if(length(cluster)>1){
# stop("If sample ist clusterd at multiple stages the number of
# Clusters at each stage must be specified!\n")
# }
#
# warning("Number of Clusters is not specified and will therefor be
# roughly estimated.
# \n Resulting bootstrap replicates might be biased. To avoid
# this define number of clusters in each strata through parameter
# 'totals'")

stop("For multistage sampling the number of PSUs at each level needs to ",
"be specified!")
}
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R/calc.stError.R:1:1: style: Lines should not be more than 80 characters.

​#' @title Calcualte point estimates and their standard errors using bootstrap weights.
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R/calc.stError.R:4:1: style: Lines should not be more than 80 characters.

​#' Calculate point estimates as well as standard errors of variables in surveys. Standard errors are estimated using bootstrap weights (see [draw.bootstrap] and [recalib]).
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:5:1: style: Lines should not be more than 80 characters.

​#' In addition the standard error of an estimate can be calcualted using the survey data for 3 or more consecutive periods, which results in a reduction of the standard error.
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R/calc.stError.R:8:1: style: Lines should not be more than 80 characters.

​#' @param dat either data.frame or data.table containing the survey data. Surveys can be a panel survey or rotating panel survey, but does not need to be. For rotating panel survey bootstrap weights can be created using [draw.bootstrap] and [recalib].
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:9:1: style: Lines should not be more than 80 characters.

​#' @param weights character specifying the name of the column in `dat` containing the original sample weights. Used to calculate point estimates.
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R/calc.stError.R:10:1: style: Lines should not be more than 80 characters.

​#' @param b.weights character vector specifying the names of the columns in `dat` containing bootstrap weights. Used to calculate standard errors.
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R/calc.stError.R:11:1: style: Lines should not be more than 80 characters.

​#' @param period character specifying the name of the column in `dat` containing the sample periods.
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R/calc.stError.R:12:1: style: Lines should not be more than 80 characters.

​#' @param var character vector containing variable names in `dat` on which `fun` shall be applied for each sample period.
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:14:1: style: Lines should not be more than 80 characters.

​#' Predefined functions are [weightedRatio], [weightedSum], but can also take any other function which returns a double or integer and uses weights as its second argument.
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R/calc.stError.R:15:1: style: Lines should not be more than 80 characters.

​#' @param national boolean, if TRUE point estimates resulting from fun will be divided by the point estimate at the national level.
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R/calc.stError.R:16:1: style: Lines should not be more than 80 characters.

​#' @param group character vectors or list of character vectors containig variables in `dat`. For each list entry `dat` will be split in subgroups according to the containing variables as well as `period`.
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R/calc.stError.R:17:1: style: Lines should not be more than 80 characters.

​#' The pointestimates are then estimated for each subgroup seperately. If `group=NULL` the data will split into sample periods by default.
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R/calc.stError.R:18:1: style: Lines should not be more than 80 characters.

​#' @param fun.adjust.var can be either `NULL` or a function. This argument can be used to apply a function for each `period` and bootstrap weight to the data. The resulting estimates will be passed down to `fun`. See details for more explanations.
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:19:1: style: Lines should not be more than 80 characters.

​#' @param adjust.var can be either `NULL` or a character specifying the first argument in `fun.adjust.var`.
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:20:1: style: Lines should not be more than 80 characters.

​#' @param period.diff character vectors, defining periods for which the differences in the point estimate as well it's standard error is calculated. Each entry must have the form of `"period1 - period2"`. Can be NULL
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:21:1: style: Lines should not be more than 80 characters.

​#' @param period.mean odd integer, defining the range of periods over which the sample mean of point estimates is additionally calcualted.
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R/calc.stError.R:22:1: style: Lines should not be more than 80 characters.

​#' @param bias boolean, if `TRUE` the sample mean over the point estimates of the bootstrap weights is returned.
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:23:1: style: Lines should not be more than 80 characters.

​#' @param size.limit integer defining a lower bound on the number of observations on `dat` in each group defined by `period` and the entries in `group`.
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R/calc.stError.R:24:1: style: Lines should not be more than 80 characters.

​#' Warnings are returned if the number of observations in a subgroup falls below `size.limit`. In addition the concerned groups are available in the function output.
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R/calc.stError.R:25:1: style: Lines should not be more than 80 characters.

​#' @param cv.limit non-negativ value defining a upper bound for the standard error in relation to the point estimate. If this relation exceed `cv.limit`, for a point estimate, they are flagged and available in the function output.
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:26:1: style: Lines should not be more than 80 characters.

​#' @param p numeric vector containing values between 0 and 1. Defines which quantiles for the distribution of `var` are additionally estimated.
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R/calc.stError.R:27:1: style: Lines should not be more than 80 characters.

​#' @param add.arg additional arguments which will be passed to fun. Can be either a named list or vector. The names of the object correspond to the function arguments and the values to column names in dat, see also examples.
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:29:1: style: Lines should not be more than 80 characters.

​#' @details `calc.stError` takes survey data (`dat`) and returns point estimates as well as their standard Errors
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R/calc.stError.R:31:1: style: Lines should not be more than 80 characters.

​#' `dat` must be household data where household members correspond to multiple rows with the same household identifier.
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R/calc.stError.R:40:1: style: Lines should not be more than 80 characters.

​#' For each variable in `var` as well as sample period the function `fun` is applied using the original as well as the bootstrap sample weights.\cr
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R/calc.stError.R:41:1: style: Lines should not be more than 80 characters.

​#' The point estimate is then selected as the result of `fun` when using the original sample weights and it's standard error is estimated with the result of `fun` using the bootstrap sample weights. \cr
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:43:1: style: Lines should not be more than 80 characters.

​#' `fun` can be any function which returns a double or integer and uses sample weights as it's second argument. The predifined options are `weightedRatio` and `weightedSum`.\cr
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:45:1: style: Lines should not be more than 80 characters.

​#' For the option `weightedRatio` a weighted ratio (in \%) of `var` is calculated for `var` equal to 1, e.g `sum(weight[var==1])/sum(weight[!is.na(var)])*100`.\cr
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:46:1: style: Lines should not be more than 80 characters.

​#' Additionally using the option `national=TRUE` the weighted ratio (in \%) is divided by the weighted ratio at the national level for each `period`.
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R/calc.stError.R:48:1: style: Lines should not be more than 80 characters.

​#' If `group` is not `NULL` but a vector of variables from `dat` then `fun` is applied on each subset of `dat` defined by all combinations of values in `group`.\cr
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R/calc.stError.R:49:1: style: Lines should not be more than 80 characters.

​#' For instance if `group = "sex"` with "sex" having the values "Male" and "Female" in `dat` the point estimate and standard error is calculated on the subsets of `dat` with only "Male" or "Female" value for "sex". This is done for each value of `period`.
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:50:1: style: Lines should not be more than 80 characters.

​#' For variables in `group` which have `NA`s in `dat` the rows containing the missings will be discarded. \cr
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R/calc.stError.R:51:1: style: Lines should not be more than 80 characters.

​#' When `group` is a list of character vectors, subsets of `dat` and the following estimation of the point estimate, including the estimate for the standard error, are calculated for each list entry.\cr
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R/calc.stError.R:53:1: style: Lines should not be more than 80 characters.

​#' The optional parameters `fun.adjust.var` and `adjust.var` can be used if the values in `var` are dependent on the `weights`. As is for instance the case for the poverty thershhold calculated from EU-SILC.
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:54:1: style: Lines should not be more than 80 characters.

​#' In such a case an additional function can be supplied using `fun.adjust.var` as well as its first argument `adjust.var`, which needs to be part of the data set `dat`. Then, before applying `fun` on variable `var`
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R/calc.stError.R:55:1: style: Lines should not be more than 80 characters.

​#' for all `period` and groups, the function `fun.adjust.var` is applied to `adjust.var` using each of the bootstrap weights seperately (NOTE: weight is used as the second argument of `fun.adjust.var`).
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R/calc.stError.R:57:1: style: Lines should not be more than 80 characters.

​#' For applying `fun` on `var` the estimates for the bootstrap replicate will now use each of the corresponding new additional variables. So instead of
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R/calc.stError.R:58:1: style: Lines should not be more than 80 characters.

​#' \deqn{fun(var,weights,...),fun(var,b.weights[1],...),fun(var,b.weights[2],...),...}
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R/calc.stError.R:60:1: style: Lines should not be more than 80 characters.

​#' \deqn{fun(var,weights,...),fun(var.1,b.weights[1],...),fun(var.2,b.weights[2],...),...}
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R/calc.stError.R:62:1: style: Lines should not be more than 80 characters.

​#' where `var.1`, `var.2`, `...` correspond to the estimates resulting from `fun.adjust.var` and `adjust.var`.
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R/calc.stError.R:63:1: style: Lines should not be more than 80 characters.

​#' NOTE: This procedure is especially usefull if the `var` is dependent on `weights` and `fun` is applied on subgroups of the data set. Then it is not possible to capture this
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R/calc.stError.R:66:1: style: Lines should not be more than 80 characters.

​#' When defining `period.diff` the difference of point estimates between periods as well their standard errors are calculated.\cr
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R/calc.stError.R:67:1: style: Lines should not be more than 80 characters.

​#' The entries in `period.diff` must have the form of `"period1 - period2"` which means that the results of the point estimates for `period2` will be substracted from the results of the point estimates for `period1`.\cr
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:69:1: style: Lines should not be more than 80 characters.

​#' Specifying `period.mean` leads to an improvement in standard error by averaging the results for the point estimates, using the bootstrap weights, over `period.mean` periods.
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R/calc.stError.R:70:1: style: Lines should not be more than 80 characters.

​#' Setting, for instance, `period.mean = 3` the results in averaging these results over each consecutive set of 3 periods.\cr
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R/calc.stError.R:71:1: style: Lines should not be more than 80 characters.

​#' Estimating the standard error over these averages gives an improved estimate of the standard error for the central period, which was used for averaging.\cr
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R/calc.stError.R:72:1: style: Lines should not be more than 80 characters.

​#' The averaging of the results is also applied in differences of point estimates. For instance defining `period.diff = "2015-2009"` and `period.mean = 3`
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R/calc.stError.R:73:1: style: Lines should not be more than 80 characters.

​#' the differences in point estimates of 2015 and 2009, 2016 and 2010 as well as 2017 and 2011 are calcualated and finally the average over these 3 differences is calculated.
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R/calc.stError.R:74:1: style: Lines should not be more than 80 characters.

​#' The periods set in `period.diff` are always used as starting periods from which `period.mean-1` consecutive periods are used to build the average.
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R/calc.stError.R:76:1: style: Lines should not be more than 80 characters.

​#' Setting `bias` to `TRUE` returns the calculation of a mean over the results from the bootstrap replicates. In  the output the corresponding columns is labeled *_mean* at the end.\cr
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R/calc.stError.R:78:1: style: Lines should not be more than 80 characters.

​#' If `fun` needs more arguments they can be supplied in `add.arg`. This can either be a named list or vector.\cr
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R/calc.stError.R:80:1: style: Lines should not be more than 80 characters.

​#' The parameter `size.limit` indicates a lower bound of the sample size for subsets in `dat` created by `group`. If the sample size of a subset falls below `size.limit` a warning will be displayed.\cr
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R/calc.stError.R:81:1: style: Lines should not be more than 80 characters.

​#' In addition all subsets for which this is the case can be selected from the output of `calc.stError` with `$smallGroups`.\cr
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R/calc.stError.R:82:1: style: Lines should not be more than 80 characters.

​#' With the parameter `cv.limit` one can set an upper bound on the coefficient of variantion. Estimates which exceed this bound are flagged with `TRUE` and are available in the function output with `$cvHigh`.
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R/calc.stError.R:83:1: style: Lines should not be more than 80 characters.

​#' `cv.limit` must be a positive integer and is treated internally as \%, e.g. for `cv.limit=1` the estimate will be flagged if the coefficient of variantion exceeds 1\%.\cr
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R/calc.stError.R:85:1: style: Lines should not be more than 80 characters.

​#' When specifying `period.mean`, the decrease in standard error for choosing this method is internally calcualted and a rough estimate for an implied increase in sample size is available in the output with `$stEDecrease`.
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R/calc.stError.R:86:1: style: Lines should not be more than 80 characters.

​#' The rough estimate for the increase in sample size uses the fact that for a sample of size \eqn{n} the sample estimate for the standard error of most point estimates converges with a factor \eqn{1/\sqrt{n}} against the true standard error \eqn{\sigma}.
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R/calc.stError.R:91:1: style: Lines should not be more than 80 characters.

​#' * `Estimates`: data.table containing period differences and/or k period averages for estimates of
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R/calc.stError.R:92:1: style: Lines should not be more than 80 characters.

​#'   `fun` applied to `var` as well as the corresponding standard errors, which are calculated using the bootstrap weights.
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:93:1: style: Lines should not be more than 80 characters.

​#'   In addition the sample size, `n`, and poplutaion size for each group is added to the output.
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R/calc.stError.R:94:1: style: Lines should not be more than 80 characters.

​#' * `smallGroups`: data.table containing groups for which the number of observation falls below `size.limit`.
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R/calc.stError.R:95:1: style: Lines should not be more than 80 characters.

​#' * `cvHigh`: data.table containing a boolean variable which indicates for each estimate if the
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R/calc.stError.R:97:1: style: Lines should not be more than 80 characters.

​#' * `stEDecrease`: data.table indicating for each estimate the theoretical increase in sample size which is
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R/calc.stError.R:98:1: style: Lines should not be more than 80 characters.

​#'   gained when averaging over k periods. Only returned if `period.mean` is not `NULL`.
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R/calc.stError.R:116:1: style: Lines should not be more than 80 characters.

​#' err.est <- calc.stError(dat_boot_calib, var = "povertyRisk", fun = weightedRatio)
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:119:1: style: Lines should not be more than 80 characters.

​#' # calculate weightedRatio for povertyRisk and fraction of one-person households per period
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R/calc.stError.R:122:1: style: Lines should not be more than 80 characters.

​#' err.est <- calc.stError(dat_boot_calib, var = c("povertyRisk", "onePerson"), fun = weightedRatio)
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:128:1: style: Lines should not be more than 80 characters.

​#' err.est <- calc.stError(dat_boot_calib, var = "povertyRisk", fun = weightedRatio, group = group)
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:131:1: style: Lines should not be more than 80 characters.

​#' # estimate weightedRatio for povertyRisk per period and gender, region and combination of both
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R/calc.stError.R:134:1: style: Lines should not be more than 80 characters.

​#' err.est <- calc.stError(dat_boot_calib, var = "povertyRisk", fun = weightedRatio, group = group)
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:139:1: style: Lines should not be more than 80 characters.

​#' err.est <- calc.stError(dat_boot_calib, var = "povertyRisk", fun = weightedRatio, period.mean = 3)
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:145:1: style: Lines should not be more than 80 characters.

​#' err.est <- calc.stError(dat_boot_calib, var = "povertyRisk", fun = weightedRatio,
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:159:1: style: Lines should not be more than 80 characters.

​#' compare.value <- dat_boot_calib[,fun(povertyRisk,pWeight,b=onePerson),by=c("year")]
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:162:1: style: Lines should not be more than 80 characters.

​#' # use a function from an other package that has sampling weights as its second argument
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R/calc.stError.R:172:1: style: Lines should not be more than 80 characters.

​#' ## make sure povertyRisk get coerced to a numeric in order to work with the external functions
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R/calc.stError.R:175:1: style: Lines should not be more than 80 characters.

​#' err.est <- calc.stError(dat_boot_calib, var = "povertyRisk", fun = help_gini, group = group,
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:180:1: style: Lines should not be more than 80 characters.

​#' # for each period and bootstrap weight before applying the weightedRatio point estimate
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R/calc.stError.R:194:1: style: Lines should not be more than 80 characters.

​#' err.est <- calc.stError(dat_boot_calib, var = "povertyRisk", fun = weightedRatio,
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:195:1: style: Lines should not be more than 80 characters.

​#'                         group = group, fun.adjust.var = povmd, adjust.var = "eqIncome",
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:214:1: style: Lines should not be more than 80 characters.

​#' err.est.different <- calc.stError(dat_boot_calib, var = "eqIncome", fun = povmd2,
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/calc.stError.R:215:1: style: Lines should not be more than 80 characters.

​#'                                   group = group, fun.adjust.var = NULL, adjust.var = NULL,
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R/calc.stError.R:234:1: style: Lines should not be more than 80 characters.

​# and calculating standard devation (using the bootstrap replicates) per period and for k-period rolling means
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R/calc.stError.R:567:1: style: Lines should not be more than 80 characters.

​# and calculating standard devation (using the bootstrap replicates) per period and for k-period rolling means
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R/computeFrac.R:3:1: style: Lines should not be more than 80 characters.

​#' Customize weight-updating within factor levels in case of numerical calibration. The
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R/computeFrac.R:10:1: style: Lines should not be more than 80 characters.

​#' which means that each weight inside the level will be multtiplied by the same factor when
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R/computeFrac.R:21:1: style: Lines should not be more than 80 characters.

​#'   \out{<center>&sum; f<sub>i</sub> w<sub>i</sub> x<sub>i</sub> = target</center>}
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R/computeFrac.R:24:1: style: Lines should not be more than 80 characters.

​#'   \out{<center>&sum; f<sub>i</sub> w<sub>i</sub> = &sum; w<sub>i</sub></center>}
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/computeFrac.R:28:1: style: Lines should not be more than 80 characters.

​#' `computeLinearG1` calculates `f` in the same way as `computeLinear`, but if `f_i*w_i<1` `f_i` will be set to `1/w_i`.
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R/computeFrac.R:35:1: style: Lines should not be more than 80 characters.

​#' @param boundLinear The output `f` will satisfy `1/boundLinear <= f <= boundLinear`. See `bound` in [ipf]
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R/demo.eusilc.R:3:1: style: Lines should not be more than 80 characters.

​#' Create a dummy dataset to be used for demonstrating the functionalities of the `surveysd` package
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R/demo.eusilc.R:4:1: style: Lines should not be more than 80 characters.

​#' based on [laeken::eusilc]. Please refer to the documentation page of the original data for
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/demo.eusilc.R:8:1: style: Lines should not be more than 80 characters.

​#' @param prettyNames Create easy-to-read names for certain variables. Recommended for demonstration
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R/demo.eusilc.R:9:1: style: Lines should not be more than 80 characters.

​#'                    purposes. Otherwise, use the original codes documented in [laeken::eusilc].
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R/demo.eusilc.R:12:1: style: Lines should not be more than 80 characters.

​#' If `prettyNames` is `TRUE`, the following variables will be available in an easy-to-read manner.
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R/demo.eusilc.R:14:1: style: Lines should not be more than 80 characters.

​#' * `hid` Household id. Consistent with respect to the reference period (`year`)
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R/demo.eusilc.R:20:1: style: Lines should not be more than 80 characters.

​#' * `ecoStat` Ecnomic status (`"part time"`, `"full time"`, `"unemployed"`, ...)
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/demo.eusilc.R:24:1: style: Lines should not be more than 80 characters.

​#' * `povertyRisk`. Logical variable determining whether a respondent is at risk of poverty
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R/draw.bootstrap.R:3:1: style: Lines should not be more than 80 characters.

​#' @description Draw bootstrap replicates from survey data with rotating panel design.
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R/draw.bootstrap.R:4:1: style: Lines should not be more than 80 characters.

​#' Survey information, like ID, sample weights, strata and population totals per strata, should be specified to ensure meaningfull survey bootstraping.
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

R/draw.bootstrap.R:7:1: style: Lines should not be more than 80 characters.

​#' @param dat either data.frame or data.table containing the survey data with rotating panel design.
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R/draw.bootstrap.R:9:1: style: Lines should not be more than 80 characters.

​#' @param hid character specifying the name of the column in `dat` containing the household id. If
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R/draw.bootstrap.R:11:1: style: Lines should not be more than 80 characters.

​#' @param weights character specifying the name of the column in `dat` containing the sample weights.
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R/draw.bootstrap.R:12:1: style: Lines should not be more than 80 characters.

​#' @param period character specifying the name of the column in `dat` containing the sample periods.
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​#'               If `NULL` (the default), it is assumed that all observations belong to the same
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​#' @param strata character vector specifying the name(s) of the column in `dat` by which the population
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​#'        was stratified. If `strata` is a vector stratification will be assumed as the combination
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​#'        of column names contained in `strata`. Setting in addition `cluster` not NULL stratification
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​#'        will be assumed on multiple stages, where each additional entry in `strata` specifies the
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​#'        stratification variable for the next lower stage. see Details for more information.
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​#' @param cluster character vector specifying cluster in the data. If not already specified in `cluster` household ID is taken es the lowest level cluster.
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​#' @param totals character specifying the name of the column in `dat` containing the the totals per strata and/or cluster. Is ONLY optional if `cluster` is `NULL` or equal `hid` and `strata` contains one columnname!
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​#' Then the households per strata will be calcualted using the `weights` argument. If clusters and strata for multiple stages are specified `totals` needs to be a vector of `length(strata)` specifying the column on `dat`
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​#' that contain the total number of PSUs at each stage. `totals` is interpreted from left the right, meaning that the first argument corresponds to the number of PSUs at the first and the last argument to the number of PSUs at the last stage.
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​#' @param single.PSU either "merge" or "mean" defining how single PSUs need to be dealt with.
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​#' For `single.PSU="merge"` single PSUs at each stage are merged with the strata or cluster with the next least number of PSUs. If multiple of those exist one will be select via random draw
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​#' For `single.PSU="mean"` single PSUs will get the mean over all bootstrap replicates at the stage which did not contain single PSUs.
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​#' @param boot.names character indicating the leading string of the column names for each bootstrap replica. If NULL defaults to "w".
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​#' @param split logical, if TRUE split households are considered using `pid`, for more information see Details.
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​#' @param pid column in `dat` specifying the personal identifier. This identifier needs to be unique for each person throught the whole data set.
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​#' @param new.method logical, if TRUE bootstrap replicates will never be negative even if in some strata the whole population is in the sample. WARNING: This is still experimental and resulting standard errors might be underestimated! Use this if for some strata the whole population is in the sample!
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​#' @return the survey data with the number of REP bootstrap replicates added as columns.
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​#' @details `draw.bootstrap` takes `dat` and draws `REP` bootstrap replicates from it.
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​#' `dat` must be household data where household members correspond to multiple rows with the same household
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​#' identifier. For most practical applications, the following columns should be available in the dataset
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​#' * Columns by which population was stratified during the sampling process (parameter: `strata`).
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​#' For single stage sampling design a column the argument `totals` is optional, meaning that a column of the number of PSUs at the first stage does not need to be supplied.
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​#' For this case the number of PSUs is calculated and added to `dat` using `strata` and `weights`. By setting `cluster` to NULL single stage sampling design is always assumed and
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R/draw.bootstrap.R:46:1: style: Lines should not be more than 80 characters.

​#' if `strata` contains of multiple column names the combination of all those column names will be used for stratification.
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​#' In the case of multi stage sampling design the argument `totals` needs to be specified and needs to have the same number of arguments as `strata`.
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​#' If `cluster` is `NULL` or does not contain `hid` at the last stage, `hid` will automatically be used as the final cluster. If, besides `hid`, clustering in additional stages is specified the number of column names in
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​#' `strata` and `cluster` (including `hid`) must be the same. If for any stage there was no clustering or stratification one can set "1" or "I" for this stage.
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​#' For example `strata=c("REGION","I"),cluster=c("MUNICIPALITY","HID")` would speficy a 2 stage sampling design where at the first stage the municipalities where drawn stratified by regions
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​#' and at the 2nd stage housholds are drawn in each municipality without stratification.
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​#' Bootstrap replicates are drawn for each survey period (`period`) using the function [rescaled.bootstrap].
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​#' Afterwards the bootstrap replicates for each household are carried forward from the first period the household enters the survey to all the censecutive periods it stays in the survey.
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​#' This ensures that the bootstrap replicates follow the same logic as the sampled households, making the bootstrap replicates more comparable to the actual sample units.
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