This page contains a summary of the data available in the AuSSA 2013 - National Identity.

To make sense of the variable names - please refer to the questionnaire which is available to download from the ADA

The complete data set is also available to download from the ADA

knitr::opts_chunk$set(
  warning = TRUE, # show warnings during codebook generation
  message = TRUE, # show messages during codebook generation
  error = TRUE, # do not interrupt codebook generation in case of errors,
                # usually better for debugging
  echo = TRUE  # show R code
)
ggplot2::theme_set(ggplot2::theme_bw())
library(codebook)
# to import an SPSS file from the same folder uncomment and edit the line below

library(haven)
library(sjlabelled)

codebook_data <- read_spss("aussa2013-codebook.sav")

#Recode can't choose to be sequential
for (col in colnames(codebook_data)) {
   if (!is.null(get_labels(codebook_data[[col]],attr.only=TRUE))) {
       labs <- get_labels(codebook_data[[col]],attr.only=TRUE)
       vals <- get_values(codebook_data[[col]])
       locator <- grep('choose',labs,ignore.case=TRUE)
       if (length(locator) != 0) {
           codebook_data[[col]] <- remove_labels(codebook_data[[col]],labels = labs[locator])
           mval <- max(vals[-locator]) + 1
           codebook_data[[col]] <- add_labels(codebook_data[[col]], labels = setNames(mval,labs[locator]))
           codebook_data[[col]][codebook_data[[col]]==vals[locator]] <- mval
       }
   }
}

# for Stata
# codebook_data <- rio::import("mydata.dta")
# for CSV
# codebook_data <- rio::import("mydata.csv")


# omit the following lines, if your missing values are already properly labelled
codebook_data <- detect_missing(codebook_data,
    only_labelled = TRUE, # only labelled values are autodetected as
                                   # missing
    negative_values_are_missing = FALSE, # negative values are missing values
    ninety_nine_problems = TRUE,   # 99/999 are missing values, if they
                                   # are more than 5 MAD from the median
    )

# If you are not using formr, the codebook package needs to guess which items
# form a scale. The following line finds item aggregates with names like this:
# scale = scale_1 + scale_2R + scale_3R
# identifying these aggregates allows the codebook function to
# automatically compute reliabilities.
# However, it will not reverse items automatically.
#codebook_data <- detect_scales(codebook_data)
metadata(codebook_data)$name <- "Australian Survey of Social Attitudes 2013 - National Identity"
metadata(codebook_data)$description <- "The Australian Survey of Social Attitudes (AuSSA) is Australia’s main source of data for the scientific study of the social attitudes, beliefs and opinions of Australians, how they change over time, and how they compare with other societies. The survey is used to help researchers better understand how Australians think and feel about their lives. It produces important information about the changing views and attitudes of Australians as we move through the 21st century. Similar surveys are run in other countries, so data from the AuSSA survey also allows us to compare Australia with countries all over the world. The aims of the survey are to discover: the range of Australians’ views on topics that are important to all of us; how these views differ for people in different circumstances; how they have changed over the past quarter century; and how they compare with people in other countries. AuSSA is also the Australian component of the International Social Survey Project (ISSP). The ISSP is a cross-national collaboration on surveys covering important topics. Each year, survey researchers in some 40 countries each do a national survey using the same questions. The ISSP focuses on a special topic each year, repeating that topic from time to time. The topic for 2013 is 'National identity'. This is the third time this has been the topic of the survey, having previously been the theme for surveys in 1995 and 2003."
metadata(codebook_data)$identifier <- "doi:10.26193/C86EZG"
metadata(codebook_data)$datePublished <- "2021-10-26"
metadata(codebook_data)$creator <- list(
      "@type" = "Person",
      givenName = "Adam", familyName = "Zammit",
      email = "adam.zammit@acspri.org.au", 
      affiliation = list("@type" = "Organization",
        name = "Australian Consortium for Social and Political Research Incorporated (ACSPRI)"))
metadata(codebook_data)$citation <- "ACSPRI (2021). AuSSA 2013 Codebook."
metadata(codebook_data)$url <- "https://www.acspri.org.au/sites/acspri.org.au/files/aussa2013codebook.html"
metadata(codebook_data)$temporalCoverage <- "2013" 
metadata(codebook_data)$spatialCoverage <- "Australia" 
codebook(codebook_data)

Metadata

Description

Dataset name: Australian Survey of Social Attitudes 2013 - National Identity

The Australian Survey of Social Attitudes (AuSSA) is Australia’s main source of data for the scientific study of the social attitudes, beliefs and opinions of Australians, how they change over time, and how they compare with other societies. The survey is used to help researchers better understand how Australians think and feel about their lives. It produces important information about the changing views and attitudes of Australians as we move through the 21st century. Similar surveys are run in other countries, so data from the AuSSA survey also allows us to compare Australia with countries all over the world. The aims of the survey are to discover: the range of Australians’ views on topics that are important to all of us; how these views differ for people in different circumstances; how they have changed over the past quarter century; and how they compare with people in other countries. AuSSA is also the Australian component of the International Social Survey Project (ISSP). The ISSP is a cross-national collaboration on surveys covering important topics. Each year, survey researchers in some 40 countries each do a national survey using the same questions. The ISSP focuses on a special topic each year, repeating that topic from time to time. The topic for 2013 is ‘National identity’. This is the third time this has been the topic of the survey, having previously been the theme for surveys in 1995 and 2003.

Metadata for search engines

name value
@type Person
givenName Adam
familyName Zammit
email
affiliation Organization , Australian Consortium for Social and Political Research Incorporated (ACSPRI)
x
A1A
A1B
A1C
A1D
A2A
A2B
A2C
A2D
A2E
A2F
A2G
A2H
A3A
A3B
A3C
A3D
A3E
A3F
A3G
A3H
A4A
A4B
A4C
A4D
A4E
A4F
A4G
A4H
A4I
A4J
A5A
A5B
A5C
A5D
A5E
A6A
A6B
A6C
A6D
A6E
A7A
A7B
A8
A9A
A9B
A9C
A9D
A9E
A9F
A9G
A9H
A10
A11
A12
A13A
A13B
A13C
A13D
A14
A15
B1A
B1B
B1C
B1D
B1E
B2A
B2B
B2C
B2D
B2E
B2F
B2G
B2H
B3A
B3B
B3C
B3D
B3E
B3F
B4
B5A
B5B
B5C
B5D
B6A
B6B
B6C
B6D
B6E
B6F
B7A
B7B
B7C
B7D
B7E
B7F
C11
C12
C13
C14
C15
C16
C17
C18
C19
C110
C111
C112
C113
C2A
C2B
C3
C4
C5
C6
C7
C8
C91
C92
C93
D1
D2A
D2B
E1
E2
E5
E6
E7
E11
E12
E13ANZSCO1
E15ANZSIC1
E16
E17
E26
E27
E28
E29
E30
E31
E32
E33
E34
E34SACC1
E35
E35SACC1
E36
E36SACC1
E38
E40A
E40B
E41A
E41B
E41C
E41D
E42A
E42B
E42C
E44
E46
E47
E48
E49
E50
state

Variables

A1A

How close do you feel to… : your town or city

Distribution

Distribution of values for A1A

Distribution of values for A1A

58 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist format.spss
A1A How close do you feel to… : your town or city numeric 58 0.9645477 1 2 5 1.926489 0.7880982 ▅▇▂▁▁ F1.0

Value labels

Response choices
name value
Very close 1
Close 2
Not very close 3
Not close at all 4
Can’t choose 5

A1B

How close do you feel to… : your State or Territory

Distribution

Distribution of values for A1B

Distribution of values for A1B

76 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist format.spss
A1B How close do you feel to… : your State or Territory numeric 76 0.9535452 1 2 5 2.035897 0.8183236 ▃▇▃▁▁ F1.0

Value labels

Response choices
name value
Very close 1
Close 2
Not very close 3
Not close at all 4
Can’t choose 5

A1C

How close do you feel to… : Australia

Distribution

Distribution of values for A1C

Distribution of values for A1C

70 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist format.spss
A1C How close do you feel to… : Australia numeric 70 0.9572127 1 1 5 1.565773 0.7152941 ▇▆▁▁▁ F1.0

Value labels

Response choices
name value
Very close 1
Close 2
Not very close 3
Not close at all 4
Can’t choose 5

A1D

How close do you feel to… : Asia

Distribution

Distribution of values for A1D

Distribution of values for A1D

101 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist format.spss
A1D How close do you feel to… : Asia numeric 101 0.9382641 1 3 5 3.265147 0.8677495 ▁▃▆▇▁ F1.0

Value labels

Response choices
name value
Very close 1
Close 2
Not very close 3
Not close at all 4
Can’t choose 5

A2A

Some people say that the following things are important for being truly Australian. Others say they are not important. How important do you think each of the following is… : to have been born in Australia

Distribution