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knit_by_pkgdown <- !is.null(knitr::opts_chunk$get("fig.retina"))
ggplot2::theme_set(ggplot2::theme_bw())
knitr::opts_chunk$set(warning = TRUE, message = TRUE, error = FALSE, echo = TRUE)
library(dplyr)
library(codebook)
In this vignette, you can see how to use the metadata that is often
already stored in SPSS and Stata files. It’s easy. All we need is the
rio::import
function. For files with the right file
extension, we can automatically pick the right way to import the data.
Here, we’re downloading straight from the Open Science Framework, so we
have to specify the file extension.
We select a subset of variables, just to keep it short. The data were shared by Emanuel Jauk in a project called How alluring are dark personalities? The Dark Triad and attractiveness in speed dating.
Often, files imported from SPSS or Stata to R will not have their
missings coded properly. Here, that is not the case, but if you find
yourself with such a dataset, the detect_missing
function
makes it easy to recognise common ways to specify missing data
(e.g. negative values, labelled values, 99/999).
darktriad <- rio::import("https://osf.io/j4fcb/download", format = "sav")
if (!knit_by_pkgdown) {
darktriad <- darktriad %>%
select(DG, sex, relStat, education, NPI_avg)
}
metadata(darktriad)$name <- "How alluring are dark personalities? The Dark Triad and attractiveness in speed dating"
metadata(darktriad)$description <- paste0("The data to this speed dating study comes in two different formats: Personwise (one record for each individual) and dyadic (pairwise; one record for each date). The respective SPSS files are named \"DarkTriadDate_person.sav\" and \"DarkTriadDate_dyad.sav\".
### Download link
[Open Science Framework](https://osf.io/j4fcb/download)
### Personwise datafile
The personwise datafile contains individual differences variables and perceiver and target effects according to the social relations model. These are centered marginal means that were calculated according to the formulae provided by Kenny, Kashy, and Cook (2006). These effects are not (!) based on multilevel analyses.
### Preprocessing
All rating variables (i.e., actual choice, friendship, short-term relationship etc.) were corrected for prior acquaintance, which means that dates wih prior acquaintance were excluded (set to missing) on a dyadic basis.
Variables are labeled in SPSS.
### A list of important abbreviations, prefixes and suffixes:
* _acq = acquaintance (i.e., variables with this suffix are controlled for prior * acquaintance)
* avg = average
* _rat = rating variable
* _z = z-standardized score
* BC = booty call
* DG = dating group (three groups in this study)
* FIPI = five item personality inventory
* FS = friendship
* FWB = friends-with-benefits
* Int = Intelligence
* Like = Likeability
* LTR = long-term relationship
* MACHIV = mach-iv machiavellianism questionnaire
* N, E, O, A, C = Big5
* NPI = narcissistic personality inventory
* ONS = one night stand
* P = perceiver
* PA = physical attractiveness
* PercEff = perceiver effect
* SD = speed dating
* SRM = social relations model
* SRP = self-report psychopathy scale
* STR = short-term relationship
* T = target
* TargEff = target effect
")
metadata(darktriad)$identifier <- "https://osf.io/jvk3u/"
metadata(darktriad)$datePublished <- "2015-10-07"
metadata(darktriad)$creator <- list(
"@type" = "Person",
givenName = "Emanuel", familyName = "Jauk",
email = "emanuel.jauk@uni‐graz.at",
affiliation = list("@type" = "Organization",
name = "Karl‐Franzens‐Universität Graz, Austria"))
metadata(darktriad)$citation <- "Jauk, E., Neubauer, A. C., Mairunteregger, T., Pemp, S., Sieber, K. P., & Rauthmann, J. F. (2016). How alluring are dark personalities? The Dark Triad and attractiveness in speed dating. European Journal of Personality, 30(2), 125-138."
metadata(darktriad)$url <- "https://osf.io/j4fcb/"
metadata(darktriad)$temporalCoverage <- "2015"
metadata(darktriad)$spatialCoverage <- "Graz, Austria"
metadata(darktriad)$distribution = list(
list("@type" = "DataDownload",
"requiresSubscription" = "https://schema.org/True",
"encodingFormat" = "https://www.loc.gov/preservation/digital/formats/fdd/fdd000469.shtml",
contentUrl = "https://osf.io/j4fcb/download")
)
# We don't want to look at the code in the codebook.
knitr::opts_chunk$set(warning = TRUE, message = TRUE, echo = FALSE)
Now, we can immediately generate a codebook.
Dataset name: How alluring are dark personalities? The Dark Triad and attractiveness in speed dating
The data to this speed dating study comes in two different formats: Personwise (one record for each individual) and dyadic (pairwise; one record for each date). The respective SPSS files are named “DarkTriadDate_person.sav” and “DarkTriadDate_dyad.sav”.
The personwise datafile contains individual differences variables and perceiver and target effects according to the social relations model. These are centered marginal means that were calculated according to the formulae provided by Kenny, Kashy, and Cook (2006). These effects are not (!) based on multilevel analyses.
All rating variables (i.e., actual choice, friendship, short-term relationship etc.) were corrected for prior acquaintance, which means that dates wih prior acquaintance were excluded (set to missing) on a dyadic basis.
Variables are labeled in SPSS.
Temporal Coverage: 2015
Spatial Coverage: Graz, Austria
Citation: Jauk, E., Neubauer, A. C., Mairunteregger, T., Pemp, S., Sieber, K. P., & Rauthmann, J. F. (2016). How alluring are dark personalities? The Dark Triad and attractiveness in speed dating. European Journal of Personality, 30(2), 125-138.
Identifier: https://osf.io/jvk3u/
Date published: 2015-10-07
Creator:
name | value |
---|---|
@type | Person |
givenName | Emanuel |
familyName | Jauk |
emanuel.jauk@uni‐graz.at | |
affiliation | Organization , Karl‐Franzens‐Universität Graz, Austria |
|
|
dating group
0 missing values.
name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | format.spss |
---|---|---|---|---|---|---|---|---|---|---|---|
DG | dating group | numeric | 0 | 1 | 1 | 2 | 3 | 2.033333 | 0.7709618 | ▆▁▇▁▆ | F8.0 |
sex
0 missing values.
name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | format.spss | display_width |
---|---|---|---|---|---|---|---|---|---|---|---|---|
sex | sex | numeric | 0 | 1 | 1 | 1 | 2 | 1.488889 | 0.502677 | ▇▁▁▁▇ | F1.0 | 5 |
name | value |
---|---|
female | 1 |
male | 2 |
relationship status
1 missing values.
name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | format.spss | display_width |
---|---|---|---|---|---|---|---|---|---|---|---|---|
relStat | relationship status | numeric | 1 | 0.9888889 | 1 | 1 | 3 | 1.089888 | 0.3247534 | ▇▁▁▁▁ | F8.0 | 10 |
name | value |
---|---|
single | 1 |
in a relationship | 2 |
living separately / divorced | 3 |
highest educational attainment
1 missing values.
name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | format.spss | display_width |
---|---|---|---|---|---|---|---|---|---|---|---|---|
education | highest educational attainment | numeric | 1 | 0.9888889 | 4 | 4 | 5 | 4.168539 | 0.3764655 | ▇▁▁▁▂ | F1.0 | 5 |
name | value |
---|---|
nine years schooling only | 1 |
professional training | 2 |
vocational school | 3 |
university-entrance diploma | 4 |
academic degree | 5 |
narcissistic personality inventory - average
0 missing values.
name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist | format.spss | display_width |
---|---|---|---|---|---|---|---|---|---|---|---|---|
NPI_avg | narcissistic personality inventory - average | numeric | 0 | 1 | 1.7 | 2.6 | 3.6 | 2.611944 | 0.3468807 | ▁▅▇▂▁ | F8.2 | 10 |
name | label | data_type | value_labels | n_missing | complete_rate | min | median | max | mean | sd | hist | format.spss | display_width |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
DG | dating group | numeric | NA | 0 | 1.0000000 | 1.0 | 2.0 | 3.0 | 2.033333 | 0.7709618 | ▆▁▇▁▆ | F8.0 | NA |
sex | sex | numeric | 1. female, 2. male |
0 | 1.0000000 | 1.0 | 1.0 | 2.0 | 1.488889 | 0.5026770 | ▇▁▁▁▇ | F1.0 | 5 |
relStat | relationship status | numeric | 1. single, 2. in a relationship, 3. living separately / divorced |
1 | 0.9888889 | 1.0 | 1.0 | 3.0 | 1.089888 | 0.3247534 | ▇▁▁▁▁ | F8.0 | 10 |
education | highest educational attainment | numeric | 1. nine years schooling only, 2. professional training, 3. vocational school, 4. university-entrance diploma, 5. academic degree |
1 | 0.9888889 | 4.0 | 4.0 | 5.0 | 4.168539 | 0.3764655 | ▇▁▁▁▂ | F1.0 | 5 |
NPI_avg | narcissistic personality inventory - average | numeric | NA | 0 | 1.0000000 | 1.7 | 2.6 | 3.6 | 2.611944 | 0.3468807 | ▁▅▇▂▁ | F8.2 | 10 |
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.