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#' @name Survey79
#'
#' @docType data
#'
#' @title Dataset containing survey details for each subject, for each year
#'
#' @description Each row represents a survey that a subject completed (or didn't complete).
#' It can be very helpful when restructuring the NLS investigator extracts into a
#' longitudinal dataset that's aligned by age (instead of by survey wave).
#' The Age variables can help to align other response variables across subjects.
#' While the 'SurveySource' indicates where to look for their responses.
#'
#' These variables are useful to many types of analyses (not just behavior genetics), and are
#' provided to save users time.
#'
#' @format A data frame with 580,752 observations on the following 6 variables.
#' * **SubjectTag** see the variable of the same name in [Links79Pair]
#' * **SurveySource** The location of that subject's survey responses that year. Values are `NoInterview`, `Gen1`, `Gen2C` or `Gen2YA`.
#' * **SurveyYear** The year/wave of the survey.
#' * **Survey79** The exact date of the administered survey.
#' * **Age** The subject's age at the time of the survey, rounded to 1 decimal.
#' See Details below.
#'
#' @details
#' `Age` uses a variable called `AgeCalculateYears` (according to a their own
#' response, or their mother's response) if it's available, and uses
#' `AgeSelfReportYears` (according to a their own response, or their mother's
#' response)
#' if not. The values usually agree, but not always.
#' These two separated variables are available for download,
#' but withheld from the R package
#' (otherwise we would exceed CRAN's maximum size).
#'
#' The exact *date* of birth isn't public (only the subject's *month* of birth).
#' To balance the downward bias of two weeks, their birthday is set to the
#' 15th day of the month to produce `AgeCalculateYears`.
#'
#' In the Gen2 Child dataset, self-reported age is
#' stated by month (eg, the child is 38 months old); a constant of 0.5 months has been added to balance the downward bias. In the Gen2 YA and
#' Gen1 datasets, self-reported age is stated by year (eg, the subject is 52 years old); a constant of 0.5 years has been added.
#'
#' @author Will Beasley
#'
#' **Download CSV**
#' If you're using the NlsyLinks package in R, the dataset is automatically available.
#' To use it in a different environment,
#' [download the csv](https://github.com/nlsy-links/NlsyLinks/blob/master/outside-data/nlsy-79/survey-79.csv?raw=true),
#' which is readable by all statistical software.
#' [links-metadata-2017-79.yml](https://github.com/nlsy-links/NlsyLinks/blob/master/outside-data/nlsy-79/links-metadata-2017-79.yml)
#' documents the dataset version information.
#'
#' @source Gen1 information comes from the Summer 2013 release of the [NLSY79 sample](https://www.nlsinfo.org/content/cohorts/nlsy79). Gen2 information
#' comes from the January 2015 release of the
#' [NLSY79 Children and Young Adults sample](https://www.nlsinfo.org/content/cohorts/nlsy79-children). Data were extracted with the NLS Investigator
#' (https://www.nlsinfo.org/investigator/).
#'
#' @keywords datasets
#'
#' @examples
#' library(NlsyLinks) # Load the package into the current R session.
#'
#' summary(Survey79)
#' table(Survey79$SurveyYear, Survey79$SurveySource)
#' table(is.na(Survey79$AgeSelfReportYears), is.na(Survey79$AgeCalculateYears))
#'
#' if (require(ggplot2) & require(dplyr)) {
#' dsSourceYear <- Survey79 %>%
#' dplyr::count(SurveyYear, SurveySource) %>%
#' dplyr::filter(SurveySource != "NoInterview")
#'
#' Survey79 %>%
#' dplyr::filter(SurveySource != "NoInterview") %>%
#' dplyr::group_by(SurveySource, SurveyYear) %>%
#' dplyr::summarize(
#' age_min = min(Age, na.rm = TRUE),
#' age_max = max(Age, na.rm = TRUE)
#' ) %>%
#' dplyr::ungroup() %>%
#' ggplot(aes(x = SurveyYear, ymin = age_min, ymax = age_max, color = SurveySource)) +
#' geom_errorbar() +
#' scale_color_brewer(palette = "Dark2") +
#' theme_minimal() +
#' theme(legend.position = c(0, 1), legend.justification = c(0, 1))
#' }
#'
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