Package 'retroharmonize' reference manual

Title:	Ex Post Survey Data Harmonization
Description:	Assist in reproducible retrospective (ex-post) harmonization of data, particularly individual level survey data, by providing tools for organizing metadata, standardizing the coding of variables, and variable names and value labels, including missing values, and documenting the data transformations, with the help of comprehensive s3 classes.
Authors:	Daniel Antal [aut, cre] , Marta Kolczynska [ctb]
Maintainer:	Daniel Antal <[email protected]>
License:	GPL-3
Version:	0.2.5.003
Built:	2024-11-25 03:24:41 UTC
Source:	https://github.com/rOpenGov/retroharmonize

Convert labelled_spss_survey vector To Factor

Description

Convert a labelled_spss_survey vector to a type of factor. Keeps only the levels and class attributes.

Usage

as_factor(x, levels = "default", ordered = FALSE)
as_factor(x, levels = "default", ordered = FALSE)

Arguments

x

Object to coerce to a factor.

levels

How to create the levels of the generated factor:

"default": uses labels where available, otherwise the values. Labels are sorted by value.
"both": like "default", but pastes together the level and value
"label": use only the labels; unlabelled values become NA
"values: use only the values

ordered

If TRUE create an ordered (ordinal) factor, if FALSE (the default) create a regular (nominal) factor.

Labelled to labelled_spss_survey

Description

Labelled to labelled_spss_survey

Usage

as_labelled_spss_survey(x, id)
as_labelled_spss_survey(x, id)

Arguments

`x`	A vector of class haven_labelled or haven_labelled_spss.
`id`	The survey identifier.

Value

A vector of labelled_spss_survey

Create a codebook

Description

This is a function candidate which will partly replace the current create_codebook function.

Usage

codebook_create()
codebook_create()

Details

This future function should create a DDI-Codebook compatible, partial codebook on survey level.

Value

This function will return

Examples

# This is a new function candidate and is not written yet.
codebook_create()
# This is a new function candidate and is not written yet.
codebook_create()

Create a codelist

Description

This is a function candidate.

Usage

codelist_create()
codelist_create()

Details

should be a new function that creates a codelist which considers https://sdmx.org/?page_id=4345 and any guidance from DDI on Question banks, and the DDI Question Construct. Partly replaces the current create_codebook function.

Value

This function will return a data frame (tbl_df) with a codelist.

Examples

# This is a new function candidate and is not written yet.
codelist_create()
# This is a new function candidate and is not written yet.
codelist_create()

Collect labels from metadata file

Description

Collect labels from metadata file

Usage

collect_val_labels(metadata)

collect_na_labels(metadata)
collect_val_labels(metadata)

collect_na_labels(metadata)

Arguments

metadata

A metadata data frame created by metadata_create.

Value

The unique valid labels or the user-defined missing labels found in all the files analyzed in metadata.

Examples

test_survey <- retroharmonize::read_rds (
   file = system.file("examples", "ZA7576.rds",
                  package = "retroharmonize"), 
   id = "test"
)
example_metadata <- metadata_create (test_survey)

collect_val_labels (metadata = example_metadata )
collect_na_labels ( metadata = example_metadata )
test_survey <- retroharmonize::read_rds (
   file = system.file("examples", "ZA7576.rds",
                  package = "retroharmonize"), 
   id = "test"
)
example_metadata <- metadata_create (test_survey)

collect_val_labels (metadata = example_metadata )
collect_na_labels ( metadata = example_metadata )

Concatenate haven_labelled_spss vectors

Description

Concatenate haven_labelled_spss vectors

Usage

concatenate(x, y)
concatenate(x, y)

Arguments

`x`	A haven_labelled_spss vector.
`y`	A haven_labelled_spss vector.

Value

A concatenated haven_labelled_spss vector. Returns an error if the attributes do not match. Gives a warning when only the variable label do not match.

Examples

v1 <- labelled::labelled(
c(3,4,4,3,8, 9),
c(YES = 3, NO = 4, `WRONG LABEL` = 8, REFUSED = 9)
)
v2 <- labelled::labelled(
  c(4,3,3,9),
  c(YES = 3, NO = 4, `WRONG LABEL` = 8, REFUSED = 9)
)
s1 <- haven::labelled_spss(
  x = unclass(v1),         # remove labels from earlier defined
  labels = labelled::val_labels(v1), # use the labels from earlier defined
  na_values = NULL,
  na_range = 8:9,
  label = "Variable Example"
)

s2 <- haven::labelled_spss(
  x = unclass(v2),         # remove labels from earlier defined
  labels = labelled::val_labels(v2), # use the labels from earlier defined
  na_values = NULL,
  na_range = 8:9,
  label = "Variable Example"
)
concatenate (s1,s2)
v1 <- labelled::labelled(
c(3,4,4,3,8, 9),
c(YES = 3, NO = 4, `WRONG LABEL` = 8, REFUSED = 9)
)
v2 <- labelled::labelled(
  c(4,3,3,9),
  c(YES = 3, NO = 4, `WRONG LABEL` = 8, REFUSED = 9)
)
s1 <- haven::labelled_spss(
  x = unclass(v1),         # remove labels from earlier defined
  labels = labelled::val_labels(v1), # use the labels from earlier defined
  na_values = NULL,
  na_range = 8:9,
  label = "Variable Example"
)

s2 <- haven::labelled_spss(
  x = unclass(v2),         # remove labels from earlier defined
  labels = labelled::val_labels(v2), # use the labels from earlier defined
  na_values = NULL,
  na_range = 8:9,
  label = "Variable Example"
)
concatenate (s1,s2)

Create a codebook

Description

Create a codebook from one or more survey data files.

Usage

create_codebook(metadata = NULL, survey = NULL)

codebook_waves_create(waves)

codebook_surveys_create(survey_list)
create_codebook(metadata = NULL, survey = NULL)

codebook_waves_create(waves)

codebook_surveys_create(survey_list)

Arguments

`metadata`	A metadata table created by `metadata_create`. Defaults to `NULL`.
`survey`	A survey data frame, defaults to `NULL`. If the survey is given as parameter, the metadata will be set to the metadata of this particular survey by `metadata_create`.
`waves`	A list of surveys.
`survey_list`	A list containing surveys of class survey.

Details

For a list of survey waves, use codebook_waves_create. The returned codebook contains only labelled variables, i.e., numeric and character types are not included, because they do not require coding.

Value

A codebook for the survey as a data frame, including the metadata, and all found SPSS-type valid or missing labels.

Examples

create_codebook (
 survey = read_rds (
          system.file("examples", "ZA7576.rds",
                      package = "retroharmonize")
          )
)

examples_dir <- system.file("examples", package = "retroharmonize")
survey_list <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]

example_surveys <- read_surveys(
  file.path( examples_dir, survey_list), 
  save_to_rds = FALSE)     

codebook_surveys_create (example_surveys)

create_codebook (
 survey = read_rds (
          system.file("examples", "ZA7576.rds",
                      package = "retroharmonize")
          )
)

examples_dir <- system.file("examples", package = "retroharmonize")
survey_list <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]

example_surveys <- read_surveys(
  file.path( examples_dir, survey_list), 
  save_to_rds = FALSE)     

codebook_surveys_create (example_surveys)

Crosswalk surveys

Description

Harmonize surveys with crosswalk tables.

Usage

crosswalk_surveys(
  crosswalk_table,
  survey_list = NULL,
  survey_paths = NULL,
  import_path = NULL,
  na_values = NULL
)

crosswalk(survey_list, crosswalk_table, na_values = NULL)
crosswalk_surveys(
  crosswalk_table,
  survey_list = NULL,
  survey_paths = NULL,
  import_path = NULL,
  na_values = NULL
)

crosswalk(survey_list, crosswalk_table, na_values = NULL)

Arguments

`crosswalk_table`	A table created with `crosswalk_table_create`, or a data frame with at least the following columns: `var_name_orig`, `var_name_target`, for harmonizing the variable names. If `val_label_orig`, `val_label_target` are present, the value labels will be harmonized, too. If `var_numeric_orig`, `var_numeric_target` are present, the numeric codes of the variable will be harmonized. If `class_target` is present, then the class of the variable will be harmonized to any of `factor`, `numeric` or `character` using `as_factor`, `as_numeric`, or `as_character`.
`survey_list`	A list of surveys imported with `read_surveys`. If set to `NULL`, the `survey_path` should give full path to the surveys.
`survey_paths`	A vector of full file paths to the surveys to subset.
`na_values`	A named vector of `na_values`, the observations that are defined to be treated as missing in the SPSS-style coding. Defaults to `NULL`.

Details

Harmonize a survey or a list of surveys with the help of a crosswalk table. You can create the crosswalk table with crosswalk_table_create, or manually create a crosswalk table as a data frame including at least the following columns: id for identifying a survey, var_name_orig for the original variable name and var_name_target for the new (target) variable name. Optionally you can harmonize the value labels, the numeric codes, and the special missing labels, too.

Value

crosswalk will return a data frame, and crosswalk_surveys a list of data frames, where the variable names, and optionally the variable labels, and the missing value range is harmonized (the same names, labels, codes are used.)

Examples


examples_dir <- system.file("examples", package = "retroharmonize")
survey_list <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]
example_surveys <- read_surveys(
  file.path( examples_dir, survey_list), 
  save_to_rds = FALSE)

## Compare with documentation:
documented_surveys <- metadata_surveys_create(example_surveys)
documented_surveys <- documented_surveys[
documented_surveys$var_name_orig %in% c( "rowid", "isocntry", "w1", "qd3_4",
                                          "qd3_8" , "qd7.4", "qd7.8", "qd6.4", "qd6.8"),
                                          ]
crosswalk_table <- crosswalk_table_create ( metadata = documented_surveys )

examples_dir <- system.file("examples", package = "retroharmonize")
survey_list <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]
example_surveys <- read_surveys(
  file.path( examples_dir, survey_list), 
  save_to_rds = FALSE)

## Compare with documentation:
documented_surveys <- metadata_surveys_create(example_surveys)
documented_surveys <- documented_surveys[
documented_surveys$var_name_orig %in% c( "rowid", "isocntry", "w1", "qd3_4",
                                          "qd3_8" , "qd7.4", "qd7.8", "qd6.4", "qd6.8"),
                                          ]
crosswalk_table <- crosswalk_table_create ( metadata = documented_surveys )

Create a crosswalk table

Description

Create a crosswalk table with the source variable names and variable labels.

Usage

crosswalk_table_create(metadata)

is.crosswalk_table(ctable)
crosswalk_table_create(metadata)

is.crosswalk_table(ctable)

Arguments

`metadata`	A metadata table created by `metadata_create`.
`ctable`	A table to validate if it is a crosswalk table.

Details

The table contains a var_name_target and val_label_target column, but these values need to be set by further manual or reproducible harmonization steps.

Value

A tibble with raw crosswalk table. It contains all harmonization tasks, but the target values need to be set by further manipulations.

Document survey item harmonization

Description

Document the current and historic coding and labelling of the variable.

Usage

document_survey_item(x)
document_survey_item(x)

Arguments

`x`	A labelled_spss_survey vector from a single survey or concatenated from several surveys.

Value

Returns a list of the current and historic coding, labelling of the valid range and missing values or range, the history of the variable names and the history of the survey IDs.

Examples

var1 <- labelled::labelled_spss(
x = c(1,0,1,1,0,8,9), 
labels = c("TRUST" = 1, 
           "NOT TRUST" = 0, 
           "DON'T KNOW" = 8, 
           "INAP. HERE" = 9), 
na_values = c(8,9))

var2 <- labelled::labelled_spss(
  x = c(2,2,8,9,1,1 ), 
  labels = c("Tend to trust" = 1, 
             "Tend not to trust" = 2, 
             "DK" = 8, 
             "Inap" = 9), 
  na_values = c(8,9))

h1 <- harmonize_values (
  x = var1, 
  harmonize_label = "Do you trust the European Union?",
harmonize_labels = list ( 
    from = c("^tend\\sto|^trust", "^tend\\snot|not\\strust", "^dk|^don", "^inap"), 
    to = c("trust", "not_trust", "do_not_know", "inap"),
  numeric_values = c(1,0,99997, 99999)), 
na_values = c("do_not_know" = 99997,
              "inap" = 99999), 
  id = "survey1",
)

h2 <- harmonize_values (
  x = var2, 
  harmonize_label = "Do you trust the European Union?",
  harmonize_labels = list ( 
    from = c("^tend\\sto|^trust", "^tend\\snot|not\\strust", "^dk|^don", "^inap"), 
    to = c("trust", "not_trust", "do_not_know", "inap"),
    numeric_values = c(1,0,99997, 99999)), 
  na_values = c("do_not_know" = 99997,
                "inap" = 99999), 
  id = "survey2"
)

h3 <- concatenate(h1, h2) 
document_survey_item(h3)
var1 <- labelled::labelled_spss(
x = c(1,0,1,1,0,8,9), 
labels = c("TRUST" = 1, 
           "NOT TRUST" = 0, 
           "DON'T KNOW" = 8, 
           "INAP. HERE" = 9), 
na_values = c(8,9))

var2 <- labelled::labelled_spss(
  x = c(2,2,8,9,1,1 ), 
  labels = c("Tend to trust" = 1, 
             "Tend not to trust" = 2, 
             "DK" = 8, 
             "Inap" = 9), 
  na_values = c(8,9))

h1 <- harmonize_values (
  x = var1, 
  harmonize_label = "Do you trust the European Union?",
harmonize_labels = list ( 
    from = c("^tend\\sto|^trust", "^tend\\snot|not\\strust", "^dk|^don", "^inap"), 
    to = c("trust", "not_trust", "do_not_know", "inap"),
  numeric_values = c(1,0,99997, 99999)), 
na_values = c("do_not_know" = 99997,
              "inap" = 99999), 
  id = "survey1",
)

h2 <- harmonize_values (
  x = var2, 
  harmonize_label = "Do you trust the European Union?",
  harmonize_labels = list ( 
    from = c("^tend\\sto|^trust", "^tend\\snot|not\\strust", "^dk|^don", "^inap"), 
    to = c("trust", "not_trust", "do_not_know", "inap"),
    numeric_values = c(1,0,99997, 99999)), 
  na_values = c("do_not_know" = 99997,
                "inap" = 99999), 
  id = "survey2"
)

h3 <- concatenate(h1, h2) 
document_survey_item(h3)

Document survey lists

Description

Document the key attributes surveys in a survey list.

Usage

document_surveys(survey_list = NULL, survey_paths = NULL, .f = NULL)

document_waves(waves)
document_surveys(survey_list = NULL, survey_paths = NULL, .f = NULL)

document_waves(waves)

Arguments

`survey_list`	A list of `survey` objects.
`survey_paths`	A vector of full file paths to the surveys to subset, defaults to `NULL`.
`.f`	A function to import the surveys with. Defaults to `'read_rds'`. For SPSS files, `read_spss` is recommended, which is a well-parameterized version of `read_spss` that saves some metadata, too. For STATA files use `read_dta`.
`waves`	A list of `survey` objects.

Details

The function has two alternative input parameters. If survey_list is the input, it returns the name of the original source data file, the number of rows and columns, and the size of the object as stored in memory. In case survey_paths contains the source data files, it will sequentially read those files, and add the file size, the last access and the last modified time attributes.

The earlier form document_waves is deprecated. Currently called document_surveys.

Value

Returns a data frame with the key attributes of the surveys in a survey list: the name of the data file, the number of rows and columns, and the size of the object as stored in memory.

Examples

examples_dir <- system.file( "examples", package = "retroharmonize")
                        
my_rds_files <- dir( examples_dir)[grepl(".rds", 
                                   dir(examples_dir))]

example_surveys <- read_surveys(file.path(examples_dir, my_rds_files))
 
documented <- document_surveys(example_surveys)

attr(documented, "original_list")
documented

document_surveys(survey_paths = file.path(examples_dir, my_rds_files))

examples_dir <- system.file( "examples", package = "retroharmonize")
                        
my_rds_files <- dir( examples_dir)[grepl(".rds", 
                                   dir(examples_dir))]

example_surveys <- read_surveys(file.path(examples_dir, my_rds_files))
 
documented <- document_surveys(example_surveys)

attr(documented, "original_list")
documented

document_surveys(survey_paths = file.path(examples_dir, my_rds_files))

Harmonize na_values in haven_labelled_spss

Description

Harmonize na_values in haven_labelled_spss

Usage

harmonize_na_values(df)
harmonize_na_values(df)

Arguments

`df`	A data frame that contains haven_labelled_spss vectors.

Value

A tibble where the na_values are consistent

Examples


examples_dir <- system.file(
    "examples", package = "retroharmonize"
    )

test_read <- read_rds ( 
     file.path(examples_dir, "ZA7576.rds"),
     id = "ZA7576", 
     doi = "test_doi")

harmonize_na_values(test_read)

examples_dir <- system.file(
    "examples", package = "retroharmonize"
    )

test_read <- read_rds ( 
     file.path(examples_dir, "ZA7576.rds"),
     id = "ZA7576", 
     doi = "test_doi")

harmonize_na_values(test_read)

Harmonize values in surveys

Description

Harmonize the value codes and value labels across multiple surveys.

Usage

harmonize_survey_values(survey_list, .f, status_message = FALSE)

harmonize_waves(waves, .f, status_message = FALSE)
harmonize_survey_values(survey_list, .f, status_message = FALSE)

harmonize_waves(waves, .f, status_message = FALSE)

Arguments

`survey_list`	A list of surveys. In the deprecated form the parameter was called `waves`.
`.f`	A function to apply for the harmonization.
`status_message`	Defaults to `FALSE`. If set to `TRUE` it shows the id of the survey that is being joined.
`waves`	A list of surveys. Deprecated.

Details

The functions binds together variables that are all present in the surveys, and applies a harmonization function .f on them. Till retroharmonize 0.2.0 called harmonize_waves.

The earlier form harmonize_waves is deprecated. The function is currently called harmonize_waves.

Value

A natural full join of all surveys in a single data frame.

Examples


examples_dir <- system.file("examples", package = "retroharmonize")
survey_list <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]

example_surveys <- read_surveys(
  file.path( examples_dir, survey_list), 
  save_to_rds = FALSE)

metadata <- lapply ( X = example_surveys, FUN = metadata_create )
metadata <- do.call(rbind, metadata)

require(dplyr)

to_harmonize <- metadata %>%
  filter ( var_name_orig %in% 
             c("rowid", "w1") |
             grepl("^trust", var_label_orig ) ) %>%
  mutate ( var_label = var_label_normalize(var_label_orig) ) %>%
  mutate ( var_name_target = val_label_normalize(var_label_orig) ) %>%
  mutate ( var_name_target = ifelse(.data$var_name_orig %in% c("rowid", "w1", "wex"), 
                                    .data$var_name_orig, .data$var_name_target) )

harmonize_eb_trust <- function(x) {
  label_list <- list(
    from = c("^tend\\snot", "^cannot", "^tend\\sto", "^can\\srely",
             "^dk", "^inap", "na"), 
   to = c("not_trust", "not_trust", "trust", "trust",
           "do_not_know", "inap", "inap"), 
    numeric_values = c(0,0,1,1, 99997,99999,99999)
  )
  
  harmonize_survey_values(x, 
                   harmonize_labels = label_list, 
                   na_values = c("do_not_know"=99997,
                                 "declined"=99998,
                                 "inap"=99999)
                   )
}

merged_surveys <- merge_surveys ( example_surveys, var_harmonization = to_harmonize  )

harmonized <- harmonize_survey_values(survey_list = merged_surveys, 
                              .f = harmonize_eb_trust,
                              status_message = FALSE)
                              
# For details see Afrobarometer and Eurobarometer Case Study vignettes.

examples_dir <- system.file("examples", package = "retroharmonize")
survey_list <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]

example_surveys <- read_surveys(
  file.path( examples_dir, survey_list), 
  save_to_rds = FALSE)

metadata <- lapply ( X = example_surveys, FUN = metadata_create )
metadata <- do.call(rbind, metadata)

require(dplyr)

to_harmonize <- metadata %>%
  filter ( var_name_orig %in% 
             c("rowid", "w1") |
             grepl("^trust", var_label_orig ) ) %>%
  mutate ( var_label = var_label_normalize(var_label_orig) ) %>%
  mutate ( var_name_target = val_label_normalize(var_label_orig) ) %>%
  mutate ( var_name_target = ifelse(.data$var_name_orig %in% c("rowid", "w1", "wex"), 
                                    .data$var_name_orig, .data$var_name_target) )

harmonize_eb_trust <- function(x) {
  label_list <- list(
    from = c("^tend\\snot", "^cannot", "^tend\\sto", "^can\\srely",
             "^dk", "^inap", "na"), 
   to = c("not_trust", "not_trust", "trust", "trust",
           "do_not_know", "inap", "inap"), 
    numeric_values = c(0,0,1,1, 99997,99999,99999)
  )
  
  harmonize_survey_values(x, 
                   harmonize_labels = label_list, 
                   na_values = c("do_not_know"=99997,
                                 "declined"=99998,
                                 "inap"=99999)
                   )
}

merged_surveys <- merge_surveys ( example_surveys, var_harmonization = to_harmonize  )

harmonized <- harmonize_survey_values(survey_list = merged_surveys, 
                              .f = harmonize_eb_trust,
                              status_message = FALSE)
                              
# For details see Afrobarometer and Eurobarometer Case Study vignettes.

Harmonize survey variables

Description

Similar to subset_surveys, but will not only remove the variables that cannot be harmonized, but also renames the variables that are kept.

Usage

harmonize_survey_variables(
  crosswalk_table,
  subset_name = "subset",
  survey_list = NULL,
  survey_paths = NULL,
  import_path = NULL,
  export_path = NULL
)
harmonize_survey_variables(
  crosswalk_table,
  subset_name = "subset",
  survey_list = NULL,
  survey_paths = NULL,
  import_path = NULL,
  export_path = NULL
)

Arguments

`crosswalk_table`	A crosswalk table created by `crosswalk_table_create` or a manually created crosstable including at least `filename`, `var_name_orig`, `var_name_target` and optionally `var_label_orig` and `var_label_target`. This parameter is optional and defaults to `NULL`.
`subset_name`	An identifier for the survey subset.
`survey_list`	A list of surveys imported with `read_surveys`. If set to `NULL`, the `survey_path` should give full path to the surveys.
`survey_paths`	A vector of full file paths to the surveys to subset.

Value

A list of surveys or save individual rds files on the export_path.

Examples

{
examples_dir <- system.file("examples", package = "retroharmonize")
survey_list  <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]
example_surveys <- read_surveys(
  file.path( examples_dir, survey_list), 
  export_path = NULL)

documented_surveys <- metadata_create(example_surveys)
documented_surveys <- documented_surveys[
   documented_surveys$var_name_orig %in% c( "rowid", "isocntry", "w1", "qd3_4",
   "qd3_8" , "qd7.4", "qd7.8", "qd6.4", "qd6.8"),
   ]
crosswalk_table    <- crosswalk_table_create ( metadata = documented_surveys )

freedom_table <- crosswalk_table[
                     which(crosswalk_table$var_name_target %in% c("rowid", "freedom")),
                     ]

harmonize_survey_variables(crosswalk_table = freedom_table,
                           subset_name     = 'freedom',
                           survey_list     = example_surveys )

}
{
examples_dir <- system.file("examples", package = "retroharmonize")
survey_list  <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]
example_surveys <- read_surveys(
  file.path( examples_dir, survey_list), 
  export_path = NULL)

documented_surveys <- metadata_create(example_surveys)
documented_surveys <- documented_surveys[
   documented_surveys$var_name_orig %in% c( "rowid", "isocntry", "w1", "qd3_4",
   "qd3_8" , "qd7.4", "qd7.8", "qd6.4", "qd6.8"),
   ]
crosswalk_table    <- crosswalk_table_create ( metadata = documented_surveys )

freedom_table <- crosswalk_table[
                     which(crosswalk_table$var_name_target %in% c("rowid", "freedom")),
                     ]

harmonize_survey_variables(crosswalk_table = freedom_table,
                           subset_name     = 'freedom',
                           survey_list     = example_surveys )

}

Harmonize the values and labels of labelled vectors

Description

Create a labelled vector with harmonized numeric coding and value labels.

Usage

harmonize_values(
  x,
  harmonize_label = NULL,
  harmonize_labels = NULL,
  na_values = c(do_not_know = 99997, declined = 99998, inap = 99999),
  na_range = NULL,
  id = "survey_id",
  name_orig = NULL,
  remove = NULL,
  perl = FALSE
)
harmonize_values(
  x,
  harmonize_label = NULL,
  harmonize_labels = NULL,
  na_values = c(do_not_know = 99997, declined = 99998, inap = 99999),
  na_range = NULL,
  id = "survey_id",
  name_orig = NULL,
  remove = NULL,
  perl = FALSE
)

Arguments

`x`	A labelled vector
`harmonize_label`	A character vector of 1L containing the new, harmonize variable label. Defaults to `NULL`, in which case it uses the variable label of `x`, unless it is also `NULL`.
`harmonize_labels`	A list of harmonization values
`na_values`	A named vector of `na_values`, the observations that are defined to be treated as missing in the SPSS-style coding.
`na_range`	A min, max range of `na_range`, the continuous missing value range. In most surveys this should be left `NULL`.
`id`	A survey ID, defaults to `survey_id`
`name_orig`	The original name of the variable. If left `NULL` it uses the latest name of the object `x`.
`remove`	Defaults to `NULL`. A character or regex that will be removed from all old value labels, like `"\("\|\)` for ( and ).
`perl`	Use perl-like regex? Defaults to FALSE.

Details

Create a labelled vector that contains in its metadata attributes the original labelling, the original numeric coding and the current labelling, with the numerical values representing the harmonized coding.

Value

A labelled vector that contains in its metadata attributes the original labelling, the original numeric coding and the current labelling, with the numerical values representing the harmonized coding.

Examples

var1 <- labelled::labelled_spss(
  x = c(1,0,1,1,0,8,9), 
  labels = c("TRUST" = 1, 
             "NOT TRUST" = 0, 
             "DON'T KNOW" = 8, 
             "INAP. HERE" = 9), 
  na_values = c(8,9))

harmonize_values (
  var1, 
  harmonize_labels = list ( 
    from = c("^tend\\sto|^trust", "^tend\\snot|not\\strust", "^dk|^don", "^inap"), 
    to = c("trust", "not_trust", "do_not_know", "inap"),
    numeric_values = c(1,0,99997, 99999)), 
    na_values = c("do_not_know" = 99997,
                "inap" = 99999), 
    id = "survey_id"
)
var1 <- labelled::labelled_spss(
  x = c(1,0,1,1,0,8,9), 
  labels = c("TRUST" = 1, 
             "NOT TRUST" = 0, 
             "DON'T KNOW" = 8, 
             "INAP. HERE" = 9), 
  na_values = c(8,9))

harmonize_values (
  var1, 
  harmonize_labels = list ( 
    from = c("^tend\\sto|^trust", "^tend\\snot|not\\strust", "^dk|^don", "^inap"), 
    to = c("trust", "not_trust", "do_not_know", "inap"),
    numeric_values = c(1,0,99997, 99999)), 
    na_values = c("do_not_know" = 99997,
                "inap" = 99999), 
    id = "survey_id"
)

Harmonize the variable names of surveys

Description

The function harmonizes the variable names of surveys (of class survey) that are imported from an external file as a wave.

Usage

harmonize_var_names(
  survey_list,
  metadata,
  old = "var_name_orig",
  new = "var_name_suggested",
  rowids = TRUE
)
harmonize_var_names(
  survey_list,
  metadata,
  old = "var_name_orig",
  new = "var_name_suggested",
  rowids = TRUE
)

Arguments

`survey_list`	A list of surveys imported with `read_surveys`
`metadata`	A metadata table created by `metadata_create` and binded together for all surveys in `survey_list`.
`old`	The column name in `metadata` that contains the old, not harmonized variable names.
`new`	The column name in `metadata` that contains the new, harmonized variable names.
`rowids`	Rename var labels of original vars `rowid` to simply `uniqid`?

Details

If the metadata that contains subsetting information is subsetted, then it will subset the surveys in survey_list.

Value

The list of surveys with harmonized variable names.

Examples

examples_dir <- system.file("examples", package = "retroharmonize")
survey_list <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]

example_surveys <- read_surveys(
  file.path( examples_dir, survey_list)
  )
  
metadata <- metadata_create(example_surveys)
metadata$var_name_suggested <- label_normalize(metadata$var_name)
metadata$var_name_suggested[metadata$label_orig == "age_education"] <- "age_education"

harmonize_var_names(survey_list = example_surveys, 
                    metadata    = metadata )
examples_dir <- system.file("examples", package = "retroharmonize")
survey_list <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]

example_surveys <- read_surveys(
  file.path( examples_dir, survey_list)
  )
  
metadata <- metadata_create(example_surveys)
metadata$var_name_suggested <- label_normalize(metadata$var_name)
metadata$var_name_suggested[metadata$label_orig == "age_education"] <- "age_education"

harmonize_var_names(survey_list = example_surveys, 
                    metadata    = metadata )

Normalize value and variable labels

Description

label_normalize removes special characters, whitespace, and other typical typing errors.

Usage

label_normalize(x)

var_label_normalize(x)

val_label_normalize(x)
label_normalize(x)

var_label_normalize(x)

val_label_normalize(x)

Arguments

`x`	A character vector of labels to be normalized.

Details

var_label_normalize and val_label_normalize removes possible chunks from question identifiers.

The functions var_label_normalize and val_label_normalize may be differently implemented for various survey series.

Value

Returns a suggested, normalized label without special characters. The var_label_normalize and val_label_normalize returns them in snake_case for programmatic use.

Examples

label_normalize (
c("Don't know", " TRUST", "DO NOT  TRUST", 
  "inap in Q.3", "Not 100%", "TRUST < 50%", 
  "TRUST >=90%", "Verify & Check", "TRUST 99%+"))
 
 var_label_normalize ( 
      c("Q1_Do you trust the national government?", 
        " Do you trust the European Commission")
        )

  val_label_normalize ( 
      c("Q1_Do you trust the national government?", 
        " Do you trust the European Commission")
        )
label_normalize (
c("Don't know", " TRUST", "DO NOT  TRUST", 
  "inap in Q.3", "Not 100%", "TRUST < 50%", 
  "TRUST >=90%", "Verify & Check", "TRUST 99%+"))
 
 var_label_normalize ( 
      c("Q1_Do you trust the national government?", 
        " Do you trust the European Commission")
        )

  val_label_normalize ( 
      c("Q1_Do you trust the national government?", 
        " Do you trust the European Commission")
        )

Labelled vectors for multiple SPSS surveys

Description

This class is amending haven::labelled_spss with a unique object identifier id to make later binding or joining reproducible and well-documented.

Usage

labelled_spss_survey(
  x = double(),
  labels = NULL,
  na_values = NULL,
  na_range = NULL,
  label = NULL,
  id = NULL,
  name_orig = NULL
)

as_character(x)

is.labelled_spss_survey(x)

as_numeric(x)
labelled_spss_survey(
  x = double(),
  labels = NULL,
  na_values = NULL,
  na_range = NULL,
  label = NULL,
  id = NULL,
  name_orig = NULL
)

as_character(x)

is.labelled_spss_survey(x)

as_numeric(x)

Arguments

`x`	A vector to label. Must be either numeric (integer or double) or character.
`labels`	A named vector or `NULL`. The vector should be the same type as `x`. Unlike factors, labels don't need to be exhaustive: only a fraction of the values might be labelled.
`na_values`	A vector of values that should also be considered as missing.
`na_range`	A numeric vector of length two giving the (inclusive) extents of the range. Use `-Inf` and `Inf` if you want the range to be open ended.
`label`	A short, human-readable description of the vector.
`id`	Survey ID
`name_orig`	The original name of the variable. If left `NULL` it uses the latest name of the object `x`.

Details

It inherits many methods from labelled, but uses more strict coercion and validation rules.

Examples

x1 <- labelled_spss_survey(
  1:10, c(Good = 1, Bad = 8), 
  na_values = c(9, 10), 
  id = "survey1")
  
is.na(x1)

# Print data and metadata 
print(x1)

x2 <- labelled_spss_survey( 1:10, 
 labels  = c(Good = 1, Bad = 8), 
 na_range = c(9, Inf),
 label = "Quality rating", 
 id = "survey1")


is.na(x2)

# Print data and metadata
x2
x1 <- labelled_spss_survey(
  1:10, c(Good = 1, Bad = 8), 
  na_values = c(9, 10), 
  id = "survey1")
  
is.na(x1)

# Print data and metadata 
print(x1)

x2 <- labelled_spss_survey( 1:10, 
 labels  = c(Good = 1, Bad = 8), 
 na_range = c(9, Inf),
 label = "Quality rating", 
 id = "survey1")


is.na(x2)

# Print data and metadata
x2

Merge surveys

Description

Merge a list of surveys into a list with harmonized variable names, variable labels and survey identifiers.

Usage

merge_surveys(survey_list, var_harmonization)

merge_waves(waves, var_harmonization)
merge_surveys(survey_list, var_harmonization)

merge_waves(waves, var_harmonization)

Arguments

`survey_list`	A list of surveys
`var_harmonization`	Metadata of surveys, including at least `filename`, `var_name_orig`, `var_name_target`, `var_label`.
`waves`	Deprecated.

Details

The function was called till version 0.2.0 merge_waves(), which reflects the vocabulary of Eurobarometer surveys.

Value

A list of surveys with harmonized names and variable labels.

Examples


examples_dir <- system.file("examples", package = "retroharmonize")
survey_list <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]

example_surveys <- read_surveys(
  file.path( examples_dir, survey_list), 
  save_to_rds = FALSE)
    
metadata <- metadata_surveys_create(example_surveys)
 
require(dplyr)

to_harmonize <- metadata %>%
  filter ( var_name_orig %in% 
             c("rowid", "w1") |
             grepl("^trust", label_orig ) ) %>%
  mutate ( var_label = var_label_normalize(label_orig) ) %>%
  mutate ( var_name_target = val_label_normalize(var_label) ) %>%
  mutate ( var_name_target = ifelse(.data$var_name_orig %in% c("rowid", "w1", "wex"), 
                                    .data$var_name_orig, .data$var_name_target) )

merge_surveys ( example_surveys, to_harmonize )

examples_dir <- system.file("examples", package = "retroharmonize")
survey_list <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]

example_surveys <- read_surveys(
  file.path( examples_dir, survey_list), 
  save_to_rds = FALSE)
    
metadata <- metadata_surveys_create(example_surveys)
 
require(dplyr)

to_harmonize <- metadata %>%
  filter ( var_name_orig %in% 
             c("rowid", "w1") |
             grepl("^trust", label_orig ) ) %>%
  mutate ( var_label = var_label_normalize(label_orig) ) %>%
  mutate ( var_name_target = val_label_normalize(var_label) ) %>%
  mutate ( var_name_target = ifelse(.data$var_name_orig %in% c("rowid", "w1", "wex"), 
                                    .data$var_name_orig, .data$var_name_target) )

merge_surveys ( example_surveys, to_harmonize )

Create a metadata table from several surveys

Description

Create a metadata table from several surveys

Usage

metadata_create(survey_list = NULL, survey_paths = NULL, .f = NULL)

metadata_waves_create(survey_list)
metadata_create(survey_list = NULL, survey_paths = NULL, .f = NULL)

metadata_waves_create(survey_list)

Arguments

inheritParams

read_surveys

Details

The form metadata_waves_create is deprecated.

Examples

examples_dir <- system.file( "examples", package = "retroharmonize")

my_rds_files <- dir( examples_dir)[grepl(".rds", 
                                        dir(examples_dir))]

example_surveys <- read_surveys(file.path(examples_dir, my_rds_files))
metadata_create (example_surveys)
examples_dir <- system.file( "examples", package = "retroharmonize")

my_rds_files <- dir( examples_dir)[grepl(".rds", 
                                        dir(examples_dir))]

example_surveys <- read_surveys(file.path(examples_dir, my_rds_files))
metadata_create (example_surveys)

Create a metadata table

Description

Create a metadata table from the survey data files.

Usage

metadata_survey_create(survey)
metadata_survey_create(survey)

Arguments

survey

A survey data frame. You receive a survey object with any importing function, i.e. read_rds, read_spss read_dta, read_csv or their common wrapper read_survey. You can construct it with survey from a data frame, too.

Details

A data frame like tibble object is returned. In case you are working with several surveys, a list of surveys or a vector of file names containing the full path to the survey must be called with metadata_create, which is a wrapper around a list of metadata_survey_create calls.

The structure of the returned tibble:

filename: The original file name; if present; missing, if a non-survey data frame is used as input survey.
id: The ID of the survey, if present; missing, if a non-survey data frame is used as input survey.
var_name_orig: The original variable name in SPSS.
class_orig: The original variable class after importing withread_spss.
var_label_orig: The original variable label in SPSS.
labels: A list of the value labels.
valid_labels: A list of the value labels that are not marked as missing values.
na_labels: A list of the value labels that refer to user-defined missing values.
na_range: An optional range of a continuous missing range, if present in the vector.
n_labels: Number of categories or unique levels, which may be different from the sum of missing and category labels.
n_valid_labels: Number of categories in the non-missing range.
n_na_labels: Number of categories of the variable, should be the sum of the former two.
na_levels: A list of the user-defined missing values.

Value

A nested data frame with metadata and the range of labels, na_values and the na_range itself.

Examples

metadata_create (
 survey_list = read_rds (
                   system.file("examples", "ZA7576.rds",
                   package = "retroharmonize")
          )
)
metadata_create (
 survey_list = read_rds (
                   system.file("examples", "ZA7576.rds",
                   package = "retroharmonize")
          )
)

Harmonize user-defined missing value ranges

Description

Harmonize the na_values attribute with na_range, if the latter is present.

Usage

na_range_to_values(x)

is.na_range_to_values(x)
na_range_to_values(x)

is.na_range_to_values(x)

Arguments

`x`	A labelled_spss or labelled_spss_survey vector

Details

na_range_to_values() tests if the function needs to be called for na_values harmonization. The na_range is often missing and less likely to cause logical problems when joining survey answers.

Value

A x with harmonized na_values and na_range attributes. If min(na_values) or max(na_values) than the left- and right-hand value of na_range, it gives a warning and adjusts the original na_range.

Examples

var1 <- labelled::labelled_spss(
  x = c(1,0,1,1,0,8,9), 
  labels = c("TRUST" = 1, 
             "NOT TRUST" = 0, 
             "DON'T KNOW" = 8, 
             "INAP. HERE" = 9), 
na_range = c(8,12))
  
na_range_to_values(var1)
as_numeric(na_range_to_values(var1))
as_character(na_range_to_values(var1))
var1 <- labelled::labelled_spss(
  x = c(1,0,1,1,0,8,9), 
  labels = c("TRUST" = 1, 
             "NOT TRUST" = 0, 
             "DON'T KNOW" = 8, 
             "INAP. HERE" = 9), 
na_range = c(8,12))
  
na_range_to_values(var1)
as_numeric(na_range_to_values(var1))
as_character(na_range_to_values(var1))

Pull a survey from a survey list

Description

Pull a survey by survey code or id.

Usage

pull_survey(survey_list, id = NULL, filename = NULL)
pull_survey(survey_list, id = NULL, filename = NULL)

Arguments

`survey_list`	A list of surveys
`id`	The id of the requested survey. If `NULL` use `filename`
`filename`	The filename of the requested survey.

Value

A single survey identified by id or filename.

Examples

examples_dir <- system.file( "examples", package = "retroharmonize")

my_rds_files <- dir( examples_dir)[grepl(".rds", 
                                   dir(examples_dir))]

example_surveys <- read_surveys(
    file.path(examples_dir, my_rds_files) )

pull_survey(example_surveys, id = "ZA5913")
examples_dir <- system.file( "examples", package = "retroharmonize")

my_rds_files <- dir( examples_dir)[grepl(".rds", 
                                   dir(examples_dir))]

example_surveys <- read_surveys(
    file.path(examples_dir, my_rds_files) )

pull_survey(example_surveys, id = "ZA5913")

Read csv file

Description

Import a survey from a csv file.

Usage

read_csv(
  file,
  id = NULL,
  doi = NULL,
  header = FALSE,
  sep = "",
  quote = "\"'",
  dec = ".",
  numerals = c("allow.loss", "warn.loss", "no.loss"),
  na.strings = "NA",
  skip = 0,
  check.names = TRUE,
  strip.white = FALSE,
  blank.lines.skip = TRUE,
  stringsAsFactors = FALSE,
  fileEncoding = "",
  encoding = "unknown"
)
read_csv(
  file,
  id = NULL,
  doi = NULL,
  header = FALSE,
  sep = "",
  quote = "\"'",
  dec = ".",
  numerals = c("allow.loss", "warn.loss", "no.loss"),
  na.strings = "NA",
  skip = 0,
  check.names = TRUE,
  strip.white = FALSE,
  blank.lines.skip = TRUE,
  stringsAsFactors = FALSE,
  fileEncoding = "",
  encoding = "unknown"
)

Arguments

`file`	A path to a file to import.
`id`	An identifier of the tibble, if omitted, defaults to the file name without its extension.
`doi`	An optional document object identifier.

Value

A tibble, data frame variant with survey attributes.

Examples

path <-  system.file("examples", "ZA7576.rds", package = "retroharmonize")
read_survey <- read_rds(path)
attr(read_survey, "id")
attr(read_survey, "filename")
attr(read_survey, "doi") 
path <-  system.file("examples", "ZA7576.rds", package = "retroharmonize")
read_survey <- read_rds(path)
attr(read_survey, "id")
attr(read_survey, "filename")
attr(read_survey, "doi")

Read Stata DTA files ('.dta') files

Description

This is a wrapper around haven::read_dta with some exception handling.

Usage

read_dta(file, id = NULL, doi = NULL, .name_repair = "unique")
read_dta(file, id = NULL, doi = NULL, .name_repair = "unique")

Arguments

`file`	A STATA file.
`id`	An identifier of the tibble, if omitted, defaults to the file name without its extension.
`doi`	An optional document object identifier.
`.name_repair`	Defaults to `"unique"` See `tibble::as_tibble` for details.

Details

'read_dta()' reads both '.dta' files.

The funcion is not yet tested.

Value

A tibble.

Variable labels are stored in the "label" attribute of each variable. It is not printed on the console, but the RStudio viewer will show it.

'write_sav()' returns the input 'data' invisibly.

Examples


path <- system.file("examples", "iris.dta", package = "haven")
read_dta(path)

path <- system.file("examples", "iris.dta", package = "haven")
read_dta(path)

Read rds file

Description

Import a survey from an rds file.

Usage

read_rds(file, id = NULL, doi = NULL)
read_rds(file, id = NULL, doi = NULL)

Arguments

`file`	A path to a file to import.
`id`	An identifier of the tibble, if omitted, defaults to the file name without its extension.
`doi`	An optional document object identifier.

Value

A tibble, data frame variant with survey attributes.

Examples

path <-  system.file("examples", "ZA7576.rds", package = "retroharmonize")
read_survey <- read_rds(path)
attr(read_survey, "id")
attr(read_survey, "filename")
attr(read_survey, "doi") 
path <-  system.file("examples", "ZA7576.rds", package = "retroharmonize")
read_survey <- read_rds(path)
attr(read_survey, "id")
attr(read_survey, "filename")
attr(read_survey, "doi")

Read SPSS ('.sav', '.zsav', '.por') files. Write '.sav' and '.zsav' files.

Description

This is a wrapper around haven::read_spss with some exception handling.

Usage

read_spss(file, user_na = TRUE, id = NULL, doi = NULL, .name_repair = "unique")
read_spss(file, user_na = TRUE, id = NULL, doi = NULL, .name_repair = "unique")

Arguments

`file`	An SPSS file.
`user_na`	Should user-defined na_values be imported? Defaults to `TRUE`.
`id`	An identifier of the tibble, if omitted, defaults to the file name without its extension.
`doi`	An optional document object identifier.
`.name_repair`	Defaults to `"unique"` See `tibble::as_tibble` for details.

Details

'read_sav()' reads both '.sav' and '.zsav' files; 'write_sav()' creates '.zsav' files when 'compress = TRUE'. 'read_por()' reads '.por' files. 'read_spss()' uses either 'read_por()' or 'read_sav()' based on the file extension.

When the SPSS file has columns which are of class labelled, but have no labels, they are read as numeric or character vectors.

Value

A tibble:

Variable labels are stored in the "label" attribute of each variable. It is not printed on the console, but the RStudio viewer will show it.

'write_sav()' returns the input 'data' invisibly.

Examples


path <- system.file("examples", "iris.sav", package = "haven")
haven::read_sav(path)

tmp <- tempfile(fileext = ".sav")
haven::write_sav(mtcars, tmp)
haven::read_sav(tmp)

path <- system.file("examples", "iris.sav", package = "haven")
haven::read_sav(path)

tmp <- tempfile(fileext = ".sav")
haven::write_sav(mtcars, tmp)
haven::read_sav(tmp)

Read survey file(s)

Description

Import surveys into a list or several .rds files.

Usage

read_surveys(survey_paths, .f = NULL, export_path = NULL)

read_survey(file_path, .f = NULL, export_path = NULL)
read_surveys(survey_paths, .f = NULL, export_path = NULL)

read_survey(file_path, .f = NULL, export_path = NULL)

Arguments

`survey_paths`	A vector of (full) file paths that contain the surveys to import.
`.f`	A function to import the surveys with. Defaults to `'NULL'`, in this case files with an extension of `'.sav'` and `'.por'` will call case `read_spss`, files with an extension of `'.dta'` will call `read_dta`, `rds` will call `read_rds` and `'.csv'` `read_csv`.
`export_path`	Defaults to `NULL`, in this case the read surveys are imported into a single list of surveys in memory. If `export_path` is a valid directory, it will instead save each survey an R object with `base::saveRDS`.

Details

Use read_survey for a single survey and read_surveys for several surveys in in a loop. The function handle exceptions with wrong file names and not readable files. If a file cannot be read, a message is printed, and empty survey is added to the the list in the place of this file.

Value

A list of the surveys or a vector of the saved file names. Each element of the list is a data frame-like survey type object where some metadata, such as the original file name, doi identifier if present, and other information is recorded for a reproducible workflow.

Examples

file1 <- system.file(
    "examples", "ZA7576.rds", package = "retroharmonize")
file2 <- system.file(
    "examples", "ZA5913.rds", package = "retroharmonize")

read_surveys (c(file1,file2), .f = 'read_rds' )
file1 <- system.file(
    "examples", "ZA7576.rds", package = "retroharmonize")
file2 <- system.file(
    "examples", "ZA5913.rds", package = "retroharmonize")

read_surveys (c(file1,file2), .f = 'read_rds' )

retroharmonize: Retrospective harmonization of survey data files

Description

The goal of retroharmonize is to facilitate retrospective (ex-post) harmonization of data, particularly survey data, in a reproducible manner. The package provides tools for organizing the metadata, standardizing the coding of variables, variable names and value labels, including missing values, and for documenting all transformations, with the help of comprehensive S3 classes.

import functions

Read data stored in formats with rich metadata, such as SPSS (.sav) files, and make them usable in a programmatic context.
read_spss: read an SPSS file and record metadata for reproducibility
read_rds: read an rds file and record metadata for reproducibility
read_surveys: programmatically read a list of surveys
pull_survey: pull a single survey from a survey list.

subsetting functions

subset_surveys: remove variables from surveys that cannot be harmonized.

variable name harmonization functions

harmonize_survey_variables: Create a list of surveys with harmonized variable names.

codebook functions

codebook_create: A not yet working function.

codelist functions

codelist_create: A not yet working function.

variable label harmonization functions

Create consistent coding and labelling.
harmonize_values: Harmonize the label list across surveys.
harmonize_survey_values: Create a list of surveys with harmonized value labels.
na_range_to_values: Make the na_range attributes, as imported from SPSS, consistent with the na_values attributes.
label_normalize removes special characters, whitespace, and other typical typing errors and helps the uniformization of labels and variable names.

survey harmonization functions

merge_surveys: Create a list of surveys with harmonized names and variable labels.
crosswalk_surveys: Create a list of surveys with harmonized variable names, harmonized value labels and harmonize R classes.
crosswalk: Create a joined data frame of surveys with harmonized variable names, harmonized value labels and harmonize R classes.

metadata functions

metadata_create: Createa metadata dataa from one or more survey.
metadata_survey_create: Create a joined metadata data frame from one survey.
create_codebook and codebook_waves_create crosswalk_table_create: Create an initial crosswalk table from a metadata data frame.

documentation functions

Make the workflow reproducible by recording the harmonization process. document_survey_item: Returns a list of the current and historic coding, labelling of the valid range and missing values or range, the history of the variable names and the history of the survey IDs. document_surveys: Document the key attributes surveys in a survey list.

type conversion functions

Consistently treat labels and SPSS-style user-defined missing values in the R language. survey helps constructing a valid survey data frame, and labelled_spss_survey helps creating a vector for a questionnaire item. as_numeric: convert to numeric values.
as_factor: convert to labels to factor levels.
as_character: convert to labels to characters.
as_labelled_spss_survey: convert labelled and labelled_spss vectors to labelled_spss_survey vectors.

Subset surveys

Description

This is a wrapper function for various procedures to reduce the size of surveys by removing variables that are not harmonized.

Usage

subset_surveys(
  survey_list,
  survey_paths = NULL,
  rowid = "rowid",
  subset_name = "subset",
  subset_vars = NULL,
  crosswalk_table = NULL,
  import_path = NULL,
  export_path = NULL
)

subset_waves(waves, subset_vars = NULL)

subset_save_surveys(
  crosswalk_table,
  subset_name = "subset",
  survey_list = NULL,
  subset_vars = NULL,
  survey_paths = NULL,
  import_path = NULL,
  export_path = NULL
)
subset_surveys(
  survey_list,
  survey_paths = NULL,
  rowid = "rowid",
  subset_name = "subset",
  subset_vars = NULL,
  crosswalk_table = NULL,
  import_path = NULL,
  export_path = NULL
)

subset_waves(waves, subset_vars = NULL)

subset_save_surveys(
  crosswalk_table,
  subset_name = "subset",
  survey_list = NULL,
  subset_vars = NULL,
  survey_paths = NULL,
  import_path = NULL,
  export_path = NULL
)

Arguments

`survey_list`	A list of surveys imported with `read_surveys`. If set to `NULL`, the `survey_path` should give full path to the surveys.
`survey_paths`	A vector of full file paths to the surveys to subset.
`rowid`	The unique row (observation) identifier in the files. Defaults to `"rowid"`, which is the default of the importing functions in this package.
`subset_name`	An identifier for the survey subset.
`subset_vars`	The names of the variables that should be kept from all surveys in the list that contains the wave of surveys. Defaults to `NULL` in which case it returns all variables without subsetting.
`crosswalk_table`	A crosswalk table created by `crosswalk_table_create` or a manually created crosstable including at least `filename`, `var_name_orig`, `var_name_target` and optionally `var_label_orig` and `var_label_target`. This parameter is optional and defaults to `NULL`.
`waves`	A list of surveys imported with `read_surveys`.

Details

This function allows several workflows. Subsetting can be based on a vector of variable names given by survey_path, or on the basis of a crosstable. The subset_save_surveys can be called directly.

subset_surveys will also harmonize the variable names if the var_name_target is optionally defined in the crosswalk_table input. harmonize_survey_variables is a wrapper and will require that the new (target) variable names are present in a valid crosstable.

Value

A list of surveys or save individual rds files on the export_path.

Examples

examples_dir <- system.file("examples", package = "retroharmonize")
survey_list <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]

example_surveys <- read_surveys(
  file.path( examples_dir, survey_list)
  )
  
subset_surveys(survey_list = example_surveys, 
               subset_vars = c("rowid", "isocntry", "qa10_1", "qa14_1"), 
               subset_name = "subset_example")
examples_dir <- system.file("examples", package = "retroharmonize")
survey_list <- dir(examples_dir)[grepl("\\.rds", dir(examples_dir))]

example_surveys <- read_surveys(
  file.path( examples_dir, survey_list)
  )
  
subset_surveys(survey_list = example_surveys, 
               subset_vars = c("rowid", "isocntry", "qa10_1", "qa14_1"), 
               subset_name = "subset_example")

Create a survey data frame

Description

Store the data of a survey in a tibble (data frame) with a unique survey identifier, import filename, and optional document object identifier.

Usage

survey(
  object = data.frame(),
  id = character(),
  filename = character(),
  doi = character()
)

is.survey(object)

## S3 method for class 'survey'
summary(object, ...)
survey(
  object = data.frame(),
  id = character(),
  filename = character(),
  doi = character()
)

is.survey(object)

## S3 method for class 'survey'
summary(object, ...)

Arguments

`object`	A tibble or data frame that contains the survey data.
`id`	A mandatory identifier for the survey.
`filename`	The import file name.
`doi`	Optional document object identifier (doi), can be omitted.
`...`	Arguments passed to summary method.

Details

Whilst you can create a survey object with this helper function, it is most likely that you will receive it with an importing function, i.e. read_rds, read_spss read_dta, read_csv or their common wrapper read_survey.

Value

A tibble with id, filename, doi metadata information.

Examples

example_survey <- survey( 
  object =data.frame ( 
    rowid = 1:6,
    observations = runif(6)), 
  id = 'example', 
  filename = "no_file"
)
example_survey <- survey( 
  object =data.frame ( 
    rowid = 1:6,
    observations = runif(6)), 
  id = 'example', 
  filename = "no_file"
)

Package 'retroharmonize'

Help Index

Convert labelled_spss_survey vector To Factor

Description

Usage

Arguments

See Also

Labelled to labelled_spss_survey

Description

Usage

Arguments

Value

See Also

Create a codebook

Description

Usage

Details

Value

Examples

Create a codelist

Description

Usage

Details

Value

Examples

Collect labels from metadata file

Description

Usage

Arguments

Value

See Also

Examples

Concatenate haven_labelled_spss vectors

Description

Usage

Arguments

Value

Examples

Create a codebook

Description

Usage

Arguments

Details

Value

See Also

Examples

Crosswalk surveys

Description

Usage

Arguments

Details

Value

See Also

Examples

Create a crosswalk table

Description

Usage

Arguments

Details

Value

See Also

Document survey item harmonization

Description

Usage

Arguments

Value

See Also

Examples

Document survey lists

Description

Usage

Arguments

Details

Value

See Also

Examples

Harmonize na_values in haven_labelled_spss

Description

Usage

Arguments