A questionnaire for the second round of the Social Impact of COVID-19 survey was conducted by the CSO from 12th-18th November. Individuals selected received an email from the CSO and were asked to complete the questionnaire online. The questionnaire asked for information on the following topics:
This survey is the fourth in a series on the Social Impact of COVID-19. The sample was generated from Labour Force Survey (LFS) respondents that agreed to be contacted for further research and provided an email address and phone number. The Labour Force Survey is a 2-stage sample design stratified using Administrative County and the Pobal HP Deprivation Index. For further information see the Labour Force Survey.
This Social Impact of COVID-19 survey is fourth such survey conducted by the CSO. The sample selection methodology resulted in a sample of 5,105 people.
All potential respondents were contacted by email and were asked to complete an online questionnaire. Data collection was closed on Wednesday 18th November 2020, at which point the achieved sample was 1,585 individuals.
Timeliness was a key priority in this survey and therefore the sample and subsequent weighting process is one of convenience to some extent. Some consideration needs to be given to the potential impact of sample design on response rates and achieved sample:
The weighting procedure outlined below was designed to adjust for possible bias in the achieved sample as much as possible.
The following weighting process was devised to counteract some of the potential bias within the sample, and to make the final weighted sample distribution as representative as possible of the population.
Stage 1: Non-response
In the first stage of the weighting process, each person in the sample was given a weight of 1. We utilised the current LFS non-response adjustment process, in which a stepwise logistic regression was conducted based on census household-level data, to generate response propensities based upon the following characteristics:
The sample is then grouped into strata based on propensity score, for which non-response adjustments were calculated and applied to each respondent.
Stage 2: Calibration
In stage 2, Q2 2020 LFS population estimates were used to benchmark the dataset across key characteristics for calibration. The non-response adjustments were inflated match overall the population total and then calibrated using CALMAR, to ensure that weighted sample distributions matched the Q2 2020 benchmark distributions for a number of key characteristics such as gender, age, education level, region, urban/rural location, household composition.
As outlined above, non-response adjustment has been used to address some of the imbalances between the original sample design and the achieved sample distribution as much as possible, and the subsequent calibration adjusts to key population totals to try and match current population distributions. However, given the non-random nature of the final sample selected, it is unlikely that we can fully account fully for bias inherent in the final sample. For this reason, caution should be taken when attempting to make inferences to the entire population from these results.
The questionnaire focused on the impact that COVID-19 has had on personal well-being, working conditions, health and lifestyle. It also covered topics such as levels of compliance with government guidelines, the impact of COVID-19 on Christmas celebrations and attitudes around international travel and regulations.
Some key analysis variables that may be included in the publication:
In 2018, the Survey on Income and Living Conditions (SILC) carried out an ad-hoc module on “Material deprivation, well-being and housing difficulties”, which itself provides comparisons with the SILC 2013 “Well-being” module. These surveys provided an interesting reference point for the Social Impact of COVID-19 surveys conducted in April and August 2020. The well-being questions in this November survey aim to provide some further insight into feelings of wellbeing in Ireland. While the methodologies across all surveys differ and care should be taken in the interpretation of trends over time, nonetheless the findings from these surveys present an important perspective on the impact of COVID19 in Ireland.
For the purposes of deriving household composition, a child was defined as any member of the household aged 17 or under. Household were then categorised as:
Marital status refers to the current marital status of the respondent. In order to achieve appropriate sample sizes for each group, the responses were grouped as:
Highest level of education attained
This classification is derived from a single question and refers to educational standards that have been attained and can be compared in some measurable way and it is included in the core LFS on an ongoing basis.
The question is phrased as follows:
What is the highest level of education or training you have ever successfully completed?
For the purposes of this publication these have been classified as follows:
Tenure status refers to the nature of the accommodation in which the individual resides. The status is provided by the respondent of the household questionnaire during the interview and responses are classified into the following two categories:
Areas are classified as Urban or Rural based on the following population densities derived from Census of Population 2016:
Population density >100,000
Population density 50,000 – 99,999
Population density 20,000 – 49,999
Population density 10,000 – 19,999
Population density 5,000 – 9,999
Population density 1,000 – 4,999
Population density <199 – 999
Rural areas in counties
The Central Statistics Office wishes to thank the participants for their co-operation in agreeing to take part in the Social Impact of COVID-19 Survey and for facilitating the collection of the relevant data.
 CALMAR is the statistical software developed by INSEE. Calmar is a SAS macro program that implements the calibration approach and adjusts weights assigned to individuals using auxiliary variables.
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