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License: AUSSDA Scientific Use Licence for data and CC BY for documentation

1,551 to 1,560 of 3,499 Results

10083_mr_en_v1_1.pdf Oct 21, 2020 - EOSC Pillar "National Initiatives" Survey (SUF edition) Adobe PDF - 393.3 KB - MD5: ebf93050b8979d0273d329705dd03e22 DocumentationMethod report Method report
10083_qu_en_v2_0.pdf.pdf Oct 21, 2020 - EOSC Pillar "National Initiatives" Survey (SUF edition) Adobe PDF - 3.6 MB - MD5: 698055b04842e56b1c509b5e867b77d0 DocumentationQuestionnaire Questionnaire
10083_ta01_en_v1_0.pdf Oct 21, 2020 - EOSC Pillar "National Initiatives" Survey (SUF edition) Adobe PDF - 739.2 KB - MD5: 97a96cedea3322e97036a2170e5cac6b Documentation Tabulation report
10083_vi01_en_v1_0.tab Oct 21, 2020 - EOSC Pillar "National Initiatives" Survey (SUF edition) Tabular Data - 88.7 KB - 3 Variables, 2645 Observations - UNF:6:M1b7TOdDioq/qcvbh4B/Yw== Documentation Variable identifiers and descriptions - machine-readable 01
10083_vi02_en_v1_0.tab Oct 21, 2020 - EOSC Pillar "National Initiatives" Survey (SUF edition) Tabular Data - 22.6 KB - 3 Variables, 686 Observations - UNF:6:5n7NuLkPyqS/LAs9N321qQ== Documentation Variable identifiers and descriptions - machine-readable 02
10083_vi03_en_v1_0.tab Oct 21, 2020 - EOSC Pillar "National Initiatives" Survey (SUF edition) Tabular Data - 4.4 KB - 3 Variables, 138 Observations - UNF:6:dkx9kE3TNVnT+5JnkHaCYA== Documentation Variable identifiers and descriptions - machine-readable 03
COVID-19 Prevalence April 2020 (SUF edition) Sep 17, 2020 - COVID-19 Pandemic Paškvan, Matea; Kowarik, Alexander; Schrittwieser, Karin; Till, Matthias; Weinauer, Marlene; Göllner, Tobias; Hartleib, Sarah; Klimont, Jeanette; Plate, Marc; Baumgartner, Irene; Edelhofer-Lielacher, Edith; Grasser, Alfred; Kytir, Josef, 2020, "COVID-19 Prevalence April 2020 (SUF edition)", https://doi.org/10.11587/FTDGA4, AUSSDA, V2, UNF:6:w7vtbLG4lYcqdukOEe4sMA== [fileUNF] Full edition for scientific use. The main purpose of the study was to identify the number of people infected with coronavirus in Austria as well as to report how people are feeling during this crisis. A representative random sample of 2800 people was drawn based on the Central Population Register of Austria (people living in Austria, excluding thos...
10093_co_de_v1_1.pdf Sep 17, 2020 - COVID-19 Prevalence April 2020 (SUF edition) Adobe PDF - 102.3 KB - MD5: 19607317647396167ed71a5194d92184 CodebookDocumentation Codebook
10093_da01_de_v1_1.tab Sep 17, 2020 - COVID-19 Prevalence April 2020 (SUF edition) Tabular Data - 1.1 MB - 137 Variables, 1577 Observations - UNF:6:VS65FmgRVPOJ6zaT1OWdOA== DataStata Core data file - STATA format - 137 Variables, 1577 Observations
10093_da01_de_v1_1.zsav Sep 17, 2020 - COVID-19 Prevalence April 2020 (SUF edition) Unknown - 161.1 KB - MD5: c0872ba9f16ab7b3edbcde27c927d5df DataSPSS Core data file - compressed SPSS format - 137 Variables, 1577 Observations

10083_mr_en_v1_1.pdf

Oct 21, 2020 - EOSC Pillar "National Initiatives" Survey (SUF edition)

Adobe PDF - 393.3 KB -

DocumentationMethod report

Method report

10083_qu_en_v2_0.pdf.pdf

Oct 21, 2020 - EOSC Pillar "National Initiatives" Survey (SUF edition)

Adobe PDF - 3.6 MB -

DocumentationQuestionnaire

Questionnaire

10083_ta01_en_v1_0.pdf

Oct 21, 2020 - EOSC Pillar "National Initiatives" Survey (SUF edition)

Adobe PDF - 739.2 KB -

Documentation

Tabulation report

10083_vi01_en_v1_0.tab

Oct 21, 2020 - EOSC Pillar "National Initiatives" Survey (SUF edition)

Tabular Data - 88.7 KB - 3 Variables, 2645 Observations -

Documentation

Variable identifiers and descriptions - machine-readable 01

10083_vi02_en_v1_0.tab

Oct 21, 2020 - EOSC Pillar "National Initiatives" Survey (SUF edition)

Tabular Data - 22.6 KB - 3 Variables, 686 Observations -

Documentation

Variable identifiers and descriptions - machine-readable 02

10083_vi03_en_v1_0.tab

Oct 21, 2020 - EOSC Pillar "National Initiatives" Survey (SUF edition)

Tabular Data - 4.4 KB - 3 Variables, 138 Observations -

Documentation

Variable identifiers and descriptions - machine-readable 03

COVID-19 Prevalence April 2020 (SUF edition)

Sep 17, 2020 - COVID-19 Pandemic

Paškvan, Matea; Kowarik, Alexander; Schrittwieser, Karin; Till, Matthias; Weinauer, Marlene; Göllner, Tobias; Hartleib, Sarah; Klimont, Jeanette; Plate, Marc; Baumgartner, Irene; Edelhofer-Lielacher, Edith; Grasser, Alfred; Kytir, Josef, 2020, "COVID-19 Prevalence April 2020 (SUF edition)", https://doi.org/10.11587/FTDGA4, AUSSDA, V2, UNF:6:w7vtbLG4lYcqdukOEe4sMA== [fileUNF]

Full edition for scientific use. The main purpose of the study was to identify the number of people infected with coronavirus in Austria as well as to report how people are feeling during this crisis. A representative random sample of 2800 people was drawn based on the Central Population Register of Austria (people living in Austria, excluding thos...

10093_co_de_v1_1.pdf

Sep 17, 2020 - COVID-19 Prevalence April 2020 (SUF edition)

Adobe PDF - 102.3 KB -

CodebookDocumentation

Codebook

10093_da01_de_v1_1.tab

Sep 17, 2020 - COVID-19 Prevalence April 2020 (SUF edition)

Tabular Data - 1.1 MB - 137 Variables, 1577 Observations -

DataStata

Core data file - STATA format - 137 Variables, 1577 Observations

10093_da01_de_v1_1.zsav

Sep 17, 2020 - COVID-19 Prevalence April 2020 (SUF edition)

Unknown - 161.1 KB -

DataSPSS

Core data file - compressed SPSS format - 137 Variables, 1577 Observations

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