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License: CC BY 4.0 Attribution 4.0 International

301 to 310 of 365 Results

10020_co_de_v1_2.pdf Dec 19, 2019 - ORF 'Sommergespräche': Strategies, Images and Issues in Political TV Interviews 1981-2016 (OA edition) Adobe PDF - 548.1 KB - MD5: 85b94f72d5dfe2c6a7de0f3ce3730a99 CodebookDocumentation Codebook - "Kategorienschema und Codieransweisung" (errata v1_1: typos corrected; errata v1_2: two missing values added to the documentation)
Replication Data for: Does name order still matter for candidates in a presidential primary poll in the US? Lack of response order effect in a web survey experiment Aug 27, 2019 - Survey Methods: Insights from the Field Mingnan, Liu, 2017, "Replication Data for: Does name order still matter for candidates in a presidential primary poll in the US? Lack of response order effect in a web survey experiment", https://doi.org/10.11587/DUUGBY, AUSSDA, V2, UNF:6:vKdmXvcjdsZ7eoif6YnVOw== [fileUNF] During elections, political polls provide critical data for the support each candidate receives. For that reason, the measurement of questions asking about candidate support has been receiving some research attention. As the online survey is increasingly becoming a widely used tool for public opinion and election polls, evaluation of the measuremen...
10015_da_en_v1_0.tab Aug 27, 2019 - Replication Data for: Does name order still matter for candidates in a presidential primary poll in the US? Lack of response order effect in a web survey experiment Tabular Data - 618.6 KB - 12 Variables, 5075 Observations - UNF:6:vKdmXvcjdsZ7eoif6YnVOw== Code Core data file - tab format - 12 Variables, 5075 Observations
10015_sx_en_v1_0.R Aug 27, 2019 - Replication Data for: Does name order still matter for candidates in a presidential primary poll in the US? Lack of response order effect in a web survey experiment R Syntax - 8.2 KB - MD5: ae180e3020e785e8fb5dd659da231fd9 Code replication R script
National election results Austria 1919 - 2017 (OA edition) Jul 24, 2019 - SORA SORA, 2019, "National election results Austria 1919 - 2017 (OA edition)", https://doi.org/10.11587/EQUDAL, AUSSDA, V1 Full edition for public use. Election results of the national elections in Austria 1919 to 2017. In the first republic at the level of the judicial districts, in the second republic at the municipal level.
10049_co_de_v1_0.pdf Jul 24, 2019 - National election results Austria 1919 - 2017 (OA edition) Adobe PDF - 309.7 KB - MD5: 719cf32fe7206ebf8bae8a7e44d2337d CodebookDocumentation Codebook
10049_da_de_v1_0.zip Jul 24, 2019 - National election results Austria 1919 - 2017 (OA edition) ZIP Archive - 5.6 MB - MD5: e34caebdf568bc60e29f9206f7c1c74f DataEXCEL Data files - Excel format; 10049_da01_de_v1_0.xlsx (1919-1930), 10049_da02_de_v1_0.xlsx (1945-2017)
Replication Data for: Building a Sampling Frame for Migrant Populations via an Onomastic Approach – Lesson learned from the Austrian Immigrant Survey 2016 Jul 4, 2019 - Survey Methods: Insights from the Field Prandner, Dimitri; Weichbold, Martin, 2019, "Replication Data for: Building a Sampling Frame for Migrant Populations via an Onomastic Approach – Lesson learned from the Austrian Immigrant Survey 2016", https://doi.org/10.11587/DIDYRW, AUSSDA, V1, UNF:6:e4yxYoEsSELMSRaP3PdwRQ== [fileUNF] Immigrants are traditionally seen as hard to survey. Their number is often too small to be analysed via data gained in general population surveys, and registers to identify them are often missing or incomplete. Therefore, researchers are forced to use alternatives for sampling. In the case of the Austrian Immigrant Survey 2016, an onomastic (name-b...
10047_da_de_v1_0.tab Jul 4, 2019 - Replication Data for: Building a Sampling Frame for Migrant Populations via an Onomastic Approach – Lesson learned from the Austrian Immigrant Survey 2016 Tabular Data - 32.8 KB - 11 Variables, 600 Observations - UNF:6:e4yxYoEsSELMSRaP3PdwRQ== Data
10047_da_de_v1_0.zsav Jul 4, 2019 - Replication Data for: Building a Sampling Frame for Migrant Populations via an Onomastic Approach – Lesson learned from the Austrian Immigrant Survey 2016 Unknown - 9.0 KB - MD5: a2f953f1cf05bbd28e871a991c38a13e DataSPSS Core data file - compressed SPSS format - 11 Variables, 600 Observations - German

10020_co_de_v1_2.pdf

Dec 19, 2019 - ORF 'Sommergespräche': Strategies, Images and Issues in Political TV Interviews 1981-2016 (OA edition)

Adobe PDF - 548.1 KB -

CodebookDocumentation

Codebook - "Kategorienschema und Codieransweisung" (errata v1_1: typos corrected; errata v1_2: two missing values added to the documentation)

Replication Data for: Does name order still matter for candidates in a presidential primary poll in the US? Lack of response order effect in a web survey experiment

Aug 27, 2019 - Survey Methods: Insights from the Field

Mingnan, Liu, 2017, "Replication Data for: Does name order still matter for candidates in a presidential primary poll in the US? Lack of response order effect in a web survey experiment", https://doi.org/10.11587/DUUGBY, AUSSDA, V2, UNF:6:vKdmXvcjdsZ7eoif6YnVOw== [fileUNF]

During elections, political polls provide critical data for the support each candidate receives. For that reason, the measurement of questions asking about candidate support has been receiving some research attention. As the online survey is increasingly becoming a widely used tool for public opinion and election polls, evaluation of the measuremen...

10015_da_en_v1_0.tab

Aug 27, 2019 - Replication Data for: Does name order still matter for candidates in a presidential primary poll in the US? Lack of response order effect in a web survey experiment

Tabular Data - 618.6 KB - 12 Variables, 5075 Observations -

Code

Core data file - tab format - 12 Variables, 5075 Observations

10015_sx_en_v1_0.R

Aug 27, 2019 - Replication Data for: Does name order still matter for candidates in a presidential primary poll in the US? Lack of response order effect in a web survey experiment

R Syntax - 8.2 KB -

Code

replication R script

National election results Austria 1919 - 2017 (OA edition)

Jul 24, 2019 - SORA

SORA, 2019, "National election results Austria 1919 - 2017 (OA edition)", https://doi.org/10.11587/EQUDAL, AUSSDA, V1

Full edition for public use. Election results of the national elections in Austria 1919 to 2017. In the first republic at the level of the judicial districts, in the second republic at the municipal level.

10049_co_de_v1_0.pdf

Jul 24, 2019 - National election results Austria 1919 - 2017 (OA edition)

Adobe PDF - 309.7 KB -

CodebookDocumentation

Codebook

10049_da_de_v1_0.zip

Jul 24, 2019 - National election results Austria 1919 - 2017 (OA edition)

ZIP Archive - 5.6 MB -

DataEXCEL

Data files - Excel format; 10049_da01_de_v1_0.xlsx (1919-1930), 10049_da02_de_v1_0.xlsx (1945-2017)

Replication Data for: Building a Sampling Frame for Migrant Populations via an Onomastic Approach – Lesson learned from the Austrian Immigrant Survey 2016

Jul 4, 2019 - Survey Methods: Insights from the Field

Prandner, Dimitri; Weichbold, Martin, 2019, "Replication Data for: Building a Sampling Frame for Migrant Populations via an Onomastic Approach – Lesson learned from the Austrian Immigrant Survey 2016", https://doi.org/10.11587/DIDYRW, AUSSDA, V1, UNF:6:e4yxYoEsSELMSRaP3PdwRQ== [fileUNF]

Immigrants are traditionally seen as hard to survey. Their number is often too small to be analysed via data gained in general population surveys, and registers to identify them are often missing or incomplete. Therefore, researchers are forced to use alternatives for sampling. In the case of the Austrian Immigrant Survey 2016, an onomastic (name-b...

10047_da_de_v1_0.tab

Jul 4, 2019 - Replication Data for: Building a Sampling Frame for Migrant Populations via an Onomastic Approach – Lesson learned from the Austrian Immigrant Survey 2016

Tabular Data - 32.8 KB - 11 Variables, 600 Observations -

Data

10047_da_de_v1_0.zsav

Jul 4, 2019 - Replication Data for: Building a Sampling Frame for Migrant Populations via an Onomastic Approach – Lesson learned from the Austrian Immigrant Survey 2016

Unknown - 9.0 KB -

DataSPSS

Core data file - compressed SPSS format - 11 Variables, 600 Observations - German

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