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ANCOVA and the Eurobarometer (63.1, Jan-Feb 2005): Country Differences in Attitudes to Science

Dataset
By: Nick Allum Published: 2015 | Product: SAGE Research Methods Datasets
Data Type: Survey
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Abstract

This dataset example introduces ANCOVA (Analysis of Covariance). This method allows researchers to compare the means of a single variable for more than two subsets of the data to evaluate whether the means for each subset are statistically significantly different from each other or not, while adjusting for one or more covariates. This technique builds on one-way ANOVA but allows the researcher to make statistical adjustments using additional covariates in order to obtain more efficient and/or unbiased estimates of groups' differences.

This example describes ANCOVA, discusses the assumptions underlying it, and shows how to compute and interpret it. We illustrate this using a subset of data from the 2005 Eurobarometer: Europeans, Science and Technology (EB63.1). Specifically, we test whether attitudes to science and faith are different ...

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About This Dataset
Data Source Citation

European Commission (2012): Eurobarometer 63.1 (Jan-Feb 2005). TNS OPINION & SOCIAL, Brussels [Producer]. GESIS Data Archive, Cologne. ZA4233 Data file Version 1.1.0, doi:10.4232/1.10965

Full title of originating dataset

Eurobarometer 63.1 (Jan-Feb 2005): Science and Technology, Social Values, and Services of General Interest

Data author(s) and affiliations

European Commission, Brussels; DG Communication Public Opinion Analysis Sector

First publication date

June 2005

Data Universe

All respondents were residents in the respective country and aged 15 and over.

Sample/sampling procedures

A multi-stage, random (probability) sampling design was used for this Eurobarometer. In the first stage, primary sampling units (PSU) were selected from each of the administrative regionals units in every country (Statistical Office of the European Community, EUROSTAT NUTS 2 or equivalent). PSU selection was systematic, with probability proportional to population size, from sampling frames stratified by the degree of urbanization. In the next stage, a cluster of starting addresses was selected from each sampled PSU, at random. Further addresses were chosen systematically using standard random route procedures as every Nth address from the initial address. In each household, a respondent was drawn, at random, following the closest birthday rule. No more than one interview was conducted in each household. They were supposed to have sufficient command of one of the respective national language(s) to answer the questionnaire.

Separate samples were drawn for Northern Ireland and East Germany.

Data collection dates

03.01.2005-17.02.2005

Time frame of analysis

03.01.2005-17.02.2005

Unit of analysis

Individual

Location covered by data

Austria (AT)

Belgium (BE)

Bulgaria (BG)

Croatia (HR)

Cyprus (CY)

Czech Republic (CZ)

Denmark (DK)

Estonia (EE)

Finland (FI)

France (FR)

Germany (DE)

Greece (GR)

Hungary (HU)

Iceland (IS)

Ireland (IE)

Italy (IT)

Latvia (LV)

Lithuania (LT)

Luxembourg (LU)

Malta (MT)

Netherlands (NL)

Norway (NO)

Poland (PL)

Portugal (PT)

Romania (RO)

Slovakia (SK)

Slovenia (SI)

Spain (ES)

Sweden (SE)

Switzerland (CH)

Turkey (TR)

United Kingdom (GB)

Links to SRM content
  • Huitema, B. (2007). Analysis of Covariance (ANCOVA). In Neil J. Salkind, & K. Rasmussen (Eds.), Encyclopedia of Measurement and Statistics. (pp. 30–33). Thousand Oaks, CA: Sage Publications, Inc. doi: http://dx.doi.org/10.4135/9781412952644.n18
  • Breukelen, G. (2010). Analysis of Covariance (ANCOVA). In Neil J. Salkind (Ed.), Encyclopedia of Research Design. (pp. 21–27). Thousand Oaks, CA: SAGE Publications, Inc. doi: http://dx.doi.org/10.4135/9781412961288.n10
  • analysis of covariance (ANCOVA). (2004). In Duncan Cramer, & D. Howitt (Eds.), The SAGE Dictionary of Statistics. (pp. 6-7). London, England: SAGE Publications, Ltd. Retrieved from http://dx.doi.org/10.4135/9780857020123.n16
List of variables

kstot

knowledge quiz score

toomuchscience

We depend too much on science and not enough on faith

solveprob

Science and technology can sort out any problem

country

Methods Map
Analysis of covariance