This page contains a summary of the data available in the AuSSA 2020 - Environment.

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("aussa2020-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)$name <- "Australian Survey of Social Attitudes 2020 - Environment"
metadata(codebook_data)$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 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 the 2020 survey is 'Environment'. This is the fourth time this has been the topic of the survey, having previously been the theme for the survey in 1993, 2000 and 2010."
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 2020 Codebook."
metadata(codebook_data)$url <- "https://www.acspri.org.au/sites/acspri.org.au/files/aussa2020codebook.html"
metadata(codebook_data)$temporalCoverage <- "2021" 
metadata(codebook_data)$spatialCoverage <- "Australia" 
codebook(codebook_data)

Metadata

Description

Dataset name: Australian Survey of Social Attitudes 2020 - Environment

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 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 the 2020 survey is ‘Environment’. This is the fourth time this has been the topic of the survey, having previously been the theme for the survey in 1993, 2000 and 2010.

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
A1
A2
A3_A
A3_B
A3_C
A3_D
A3_E
A4
A5
A6
A7_A
A7_B
A7_C
A7_D
A8
A9
A10
A11_A
A12_A
A13_A
A13_B
A13_C
A13_D
A13_E
A13_F
A14_A
A14_B
A14_C
A14_D
A15_A
A15_B
A15_C
A15_D
A15_E
A15_F
A15_G
A16_A
A16_B
A16_C
A16_D
A16_E
A16_F
A16_G
A17
A18
A19
A20
A21
A22
A23
A24
A25
A26
A27
A28_A
A28_B
A28_C
A29_A
A29_B
A29_C
K1
K2
K5
K6
K7
K13ANZSCO1
K15ANZSIC1
K16
K27
K28
K31
K32
K33
K34
K35
K35SACC1
K36
K36SACC1
K37
K37SACC1
K39
K41
K42
K43
K44
K45
K48
K49
K50
K51
K52
state
fedelectorate
sweight

Variables

A1

Which of these issues is the most important for Australia today? :

Distribution

Distribution of values for A1

Distribution of values for A1

17 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist format.spss
A1 Which of these issues is the most important for Australia today? : numeric 17 0.9853701 1 4 10 4.053275 2.479946 ▇▇▆▁▂ F2.0

Value labels

Response choices
name value
Health care 1
Education 2
Crime 3
The environment 4
Immigration 5
The economy 6
Terrorism 7
Poverty 8
None of these 9
Cant choose 10

A2

Which is the next most important? :

Distribution

Distribution of values for A2

Distribution of values for A2

13 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist format.spss
A2 Which is the next most important? : numeric 13 0.9888124 1 3 10 3.771105 2.608082 ▇▅▃▂▁ F2.0

Value labels

Response choices
name value
Health care 1
Education 2
Crime 3
The environment 4
Immigration 5
The economy 6
Terrorism 7
Poverty 8
None of these 9
Cant choose 10

A3_A

How much do you agree or disagree with each of these statements? : Private enterprise is the best way to solve Australias economic problems

Distribution