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Note:
/ DE: *Own calculation based on data of Microcensus 2011; figures provided by the German Federal Statistical Office.
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Weighting factor
No total weight usable for international comparism.
NATIONAL weighting procedures/ variables used for calculation of NATIONAL weights:
CH DK IL JP MX NO SE SI TR: No weighting.
AR: The weights were obtained by a crosstab of sex, population or city size (three groups: 1) Buenos Aires Metropolitan Area, 2) Large and middle-large cities, 3) Middle, smaller cities and rural places), and three educational levels (1) up to complete primary, 2) secondary and incomplete tertiary, 3) complete tertiary and undergraduate and graduate university studies.
AT: Region, Sex x Age, Education, Vote last election.
AU: A post-stratification or non-response weight was calculated with the aim of rebalancing the Australian sample so the weighted sample frequencies are equal to the expected frequencies in population in a the three-way tabulation by age group (five groups), sex, and highest level of education (five levels) To avoid extreme weights, the weights were trimmed at the 1 per cent and 99 per cent level, before being rescaled so that they averaged to one across all cases in each subsample.
BE: In order to deliver one integrated harmonized data file for Belgium post stratification weights were calculated based upon age (three age groups: 18-39; 40-59; 60+), sex, and geographical classification (NUTS1 Flemish Region, Walloon Region, Brussels Capital Region). The result of this weighting procedure in combination with the sampling design is that the weights for respondents of the Brussels Capital Region are much smaller than the weights for the respondents of the Flemish and Walloon regions. The use of adequate software is always necessary when analysing data with weights, but with these data it is vitally important when comparing the regions or analysing only one region separately.
BG: Weighting variable has been computed and accounts for sex, settlement and age-groups. There are twenty coefficients - 4 groups (male and female for towns and villages) multiplied by five age groups (18-24 years, 25-34 years, 35-44 years, 45-54 years, 55-64 years, 65-84 years, 85 years and over).
CL: A weighting procedure is applied in order to correct for distortions in 2007 the representativeness of the sample as regards three variables of interest: Gender, Age, (grouped in five categories: 18-24 years, 25- 34, 35-44, 45-54, 55 or older) and Urbanity (classification of place of residence as urban or rural). The expected distribution is obtained from the 2002 census data provided by the National Institute of Statistics.
CZ: Design weights based on proportion of household sizes. The weight was derived from data of the Czech Statistical Office. Post-stratification weight based on region, community size, sex, age and education. The weight was derived from data of the Czech Statistical Office.
DE: Two separate samples for Germany. The sample for eastern Germany deliberately over-samples the five eastern federal states. If all of Germany is taken as the unit of analysis (rather than the eastern and western states), the design weight is necessary (included in the data set: weighting factor for Western Germany=1,19943949*; weighting factor for Eastern Germany=0,56823852*).
ES: Design weight calculated using autonomous communities and size of municipalities.
FI: gender; age classes (15–24, …, 65–74); NUTS3 regions with following modifications: the Greater Helsinki Area was dealt as a separate region; type of community (urban - semi-urban - rural). Weight expands the results to the population level (the sum of the weights is the size of the population aged 15 to 74).
FR: Post stratification weighting computed on sex, age (4 groups: 18 to 29 years old, 30 to 39 years old, 40 to 54 years old, 55 years old or more) and occupation (6 groups : Farmers, Tradesmen, Shopkeepers and Business Owners; Managers and Secondary/University Teachers, Intermediate Professions, White Collar Workers, Blue Collar Workers, Unemployed).
GB-GBN: The weighting reflects the relative selection probabilities of the individual at the three main stages of selection: address, DU and individual. A number of area level and interviewer observation variables were used to model response. Weights needed to be applied to correct for unequal probability to be selected (one person interviewed at each address independently from household size). Non-response weighting then applied to correct for unequal probability of response in different sub-groups in population. The final stage of weighting was to adjust the final non-response weight so that the weighted respondent sample matched the population in terms of age, sex and region. Very large weights were capped and were scaled to make the weighted sample size equal to the unweighted sample size.
IE: Post-Stratified weights. Information on the known characteristics of the national population including sex distribution, age distribution, employment status and education level were gleaned from the 'Quarterly National Household Survey, Quarter 4: 2012' as published by the Central Statistics Office (CSO) of Ireland. The figures for each of these categories in the net sample were pro-rated to the national population sample.
IN: Multiple weighting done on following variables: Age, gender, social status, income, education.
IS: Used variables: Gender, Age, IS_REG.
KR: Used variables: Sex, Age. As such, the distribution of respondents’ sex and age in the weighted dataset corresponds to that of the total population on the 2010 Census.
LT: Design weight based on sex, age and type of settlement rescaled to net sample size.
LV: Data were weighted according to the inverse probability of respondent being selected and to account for different non-response patterns in various age (10-year) and gender groups. Variables used: Sex and age.
NL: A post-stratification weight was developed using (A) information from the sampling frame, (B) information from the household roster (C) comparison with election results. No other national benchmark was used.
NO: No weighting procedure (in net sample younger people, single (never married) and people with lower education underrepresented).
PH: Weighting variable is based on people aged 18 and above and region (NCR, Balance Luzon, Visayas, Mindanao). The weight applied was based on the 2010 census population. Computed by area.
PL: Calculation of weight using IPF (Iterative Proportional Fitting) algorithm including sex, age categories (18-24, 25-34, 35-49, 50-59, 60 and more years), type of the place of living and voivodship.
PT: Calculation of weight by using AGE, SEX, PT_DEGR.
RU: Variables age, sex and education used for calculation of weight.The weighting procedure is based on the Census 2010.
SK: Weight constructed according the population characteristics sex, age groups, education, ethnicity (nationality), size of community and region. The un-weighted sample under-represents younger respondents (25-34 and 18 - 24) and over-represents residents in settlements with 1001 to 5000 inhabitants and under-represents respondents in settlements with more than 100 thousands inhabitants.
TW: Weighting factor is designed on sex, age, urbanization and education degree groups. Weights were then generated to match the population characteristics of Taiwan area.
US: The weight variable takes into consideration the sub-sampling of non-respondents and the number of adults in the household. The GSS uses a sub-sampling design to focus resources on a smaller set of the difficult cases for further attempts, thereby reducing non-response bias. It also essentially maintains the original sample size. It also adjusts for attrition.
VE: To take account of selection probabilities for individuals.
ZA: Explicit stratification variables: Province, population group and geography type (viz. urban formal, urban informal, tribal and rural formal, including commercial farms). Non-response adjustment = number of drawn HHs per EA / number of responding HHs (i.e. where a person 16+ is successfully interviewed) provided that at least 50% of households responded. Otherwise two similar (i.e. in the same explicit stratum) and neighbouring EAs are combined and a combined adjustment factor calculated.
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