Irish Social Science Data Archive
Housing Agency - Studies of Irish Housing Experiences, Attitudes & Aspirations
Study number (SN): 0072-02
The Housing Agency (2021). Housing experience, attitudes and aspirations of Irish Apartment Residents, 2019 [dataset]. Version 1. Dublin: Irish Social Science Data Archive SN: 0072-02. https://www.ucd.ie/issda/data/housingexperienceattitudesandaspirationsofirishhouseholds/irishhousingexperiences2019/ |
Part of The Housing Agency National Housing Study of Irish Housing Experiences, Attitudes and Aspirations in Ireland.
The purpose of the research study was to provide information on the experiences, attitudes and aspirations of apartment dwellers in Ireland in 2019. The focus was on those living in purpose-built flats or apartments and examines people’s levels of satisfaction with their apartment and neighbourhood, affordability issues, and explores housing aspirations for the future. No distinction is made between flat or apartment in the analysis. The research objectives were to:
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Individuals aged 19 years and older living in purpose-built apartment blocks in Ireland, as defined in the MUD ACT 2011. One respondent per apartment.
The CSO provides information for apartment dwellers in private households from the age of 19 and over (instead of 18 and over used for standard nationally representative studies). As a consequence, the sampling structure for Irish adults living in purpose-built apartments was based on a nationally representative sample of adults age 19 and over.
From 06/2019 to 08/2019
Cross-sectional one-time study
Country: Ireland
The sampling approach taken was non-probability quota similar to the 2018 study. In the 2018 Housing Agency study, AIMRO social class quotas were used to ensure the sample matched the Irish population. In the absence of this, social class quotas for those living in purpose-built apartments; the Pobal HP Deprivation Index was used to ensure that a spread of socio-economic groups were interviewed.
The achieved sample was 511 completed survey questionnaires from a sample which was representative of the Irish population aged 19 years plus living in purpose-built apartment blocks. To achieve this, quotas were set on age, region and gender to align with the Central Statistic Office’s Census 2016.
Sampling points were spread to represent the distribution of apartment dwellers nationally – across Dublin, the rest of Leinster, Munster, Connacht and Ulster. Furthermore, within Dublin sampling points were distributed across the four local authority areas proportionally to represent the number of persons living in purpose-built apartment blocks in each administrative area.
To reflect the diversity of Dublin and to take account of the large proportion of interviews to be conducted in the capital, the Pobal HP Deprivation Index (https://www.pobal.ie/app/uploads/2018/06/The-2016-Pobal-HP-Deprivation-Index-Introduction-07.pdf) which shows the relative affluence or disadvantage of a particular geographical area, was used to profile each local authority area and determine the spread of sampling points within each local authority area. Using this method ensured the interviewing captured a representative socio-economic profile in each local authority area.
A pilot study of 24 completed face-to-face interviews was undertaken across three sampling points in Dublin and carried out prior to main stage data collection. This approach highlighted any potential issues that could affect data quality and fieldwork efficiencies. Findings from the pilot study informed the main stage interviewer briefings. As changes were made to the questionnaire following the pilot study, the data collected from the 24 interviews was excluded.
Interviewers achieved access to gated apartment blocks by liaising with a resident and/ or security personnel where possible. In cases where access was not possible or refused, interviewers sought access to another apartment development within the assigned electoral district where possible. If a different apartment development could not be accessed, an alternate electoral district and starting address was allocated. The alternative electoral district had the same deprivation score as the original electoral district.
The sampling point selection process used the Pobal HP Deprivation Index. The following table details the stages taken in the selection of sampling points and starting addresses:
Table 1. Sampling point selection process
Stage |
Details |
1 |
Calculate number of sampling points in each region based on the proportion of persons living in a flat or apartment in a purpose-built block as per CSO Census 2016. |
2 |
Calculate number of sampling points in each Dublin local authority based on the proportion of persons living in a flat or apartment in a purpose-built block. |
3 |
Download CSO database of number of persons accommodated in apartments. |
4 |
Download the Deprivation Index data for Dublin region. https://maps.pobal.ie/WebApps/GeoprofilingReports/index.html |
5 |
Determine deprivation profile of each local authority area and distribute sampling points proportionally to deprivation scores and classify each ‘Electoral Division’ within Dublin with a Deprivation Index Score Class ranging from -4 to 4. |
7 |
Select sampling points with the highest number of persons accommodated in apartments that meet the criteria of Deprivation Index score class by local authority |
8 |
Identify ‘Electoral districts’ within the points above with the highest number of persons accommodated in apartments to target the population more easily. |
9 |
Select starting address using CSO SapMap by displaying each ‘Small Area’ and using Eircode finder website to target the apartments. |
The following table outlines the proportional distribution of population of apartment dwellers and sampling points in the four Dublin local authorities by Deprivation Index score:
Table 2: Number of sampling points and deprivation score
Deprivation Score |
No. Sampling Points per Local authority |
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Class |
Area Classification |
Dublin City |
Dún Laoghaire-Rathdown |
Fingal |
South Dublin |
-4 |
Extremely disadvantaged |
0 |
0 |
0 |
0 |
-3.0 |
Very disadvantaged |
0 |
0 |
0 |
0 |
-2.0 |
Disadvantaged |
3 |
0 |
0 |
2 |
-1.0 |
Marginally below average |
6 |
1 |
1 |
1 |
1.0 |
Marginally above average |
8 |
2 |
5 |
1 |
2.0 |
Affluent |
5 |
3 |
1 |
1 |
3.0 |
Very affluent |
0 |
0 |
0 |
0 |
4 |
Extremely affluent |
0 |
0 |
0 |
0 |
A three-stage sample selection procedure was used. The stages in the sample selection were:
• Stage 1: Selection of a fixed number of sampling points
• Stage 2: Selection of starting addresses within sampling points
• Stage 3: Selection of the individual for interview
Stage 1: Selection of sampling points
The regional spread of sampling points was proportionate to the number of those living in a flat or apartment in a purpose-built block. The sampling points were stratified using two indicators of socio-demographic and socio-economic composition: the Pobal HP Deprivation Index and the CSO’s area typology for the four Dublin local authorities.
Stage 2: Selection of starting addresses within sampling points
Apartment developments were identified beforehand using the Eircode finder. A single point address with multiple Eircodes was used to identify purpose-built apartment blocks. Interviewers were given a starting address within the purpose-built apartment development, the Eircode and the Electoral District name. Maps were provided to ensure interviews were conducted within Electoral District boundaries only.
To ensure sample representation of local authority (LA) owned and approved housing body (AHB) apartments, twelve sampling points were given a local authority or AHB starting address. All other sampling points were given private apartment addresses.
Stage 3: Selection of the individual for interview
When contacting the household, the interviewer sought an adult resident aged 19 years or older with whom to complete the screening question. Prior to the interview taking place, informed consent was sought from the person taking the interview. Once this individual was identified and had provided consent, the interviewer conducted the interview.
QNEWREGIONQ Province/Capital location
Quota variables
Gender
QC4
Age
QcD Agegroups
QB Age
Socioeconomic group
QNEWRENTQ Socio-economic groups
While all efforts were made to achieve a wholly representative survey sample, some variables are weighted to match that recorded by the CSO 2016 census of population broken down by age, sex, region and tenure type. Due to weighting of data to reflect CSO figures, some base sizes may vary by +/- 1. Individual weights were applied to ‘private renters’ and LA/ AHB renters within the ‘social renter’ classification.
SPSS syntax to apply weight for a nationally representative sample:
WEIGHT BY WEIGHT.
Non-response data (e.g. refusals, derelict house etc.) was not recorded. A true non-response rate is unable to be calculated as the sample was not a probability sample.
File name
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File format/s |
Contents of file |
0072-02_IrishApartmentResidents_2019 |
.sav |
Housing Agency 2019 survey dataset |
0072-02_IrishApartmentResidents_2019 |
.dat |
Housing Agency 2019 survey dataset |
0072-02_IrishApartmentResidents_2019 |
.dta |
Housing Agency 2019 survey dataset |
File name |
File format/s |
Contents of file |
2019 Housing Agency Survey information sheet and consent form |
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Information sheet and blank consent form |
2019 Housing Agency Residential Satisfaction Questionnaire Apartments |
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Questionnaire |
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Codebook |
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Housing Agency Publication |
https://www.housingagency.ie/publications
Molloy, R., McAnulty, U., Healy, S. & Murphy, A. (2019). Apartment Living in Ireland 2019. National Study of Irish Housing Experiences, Attitudes and Aspirations in Ireland, Dublin: Housing Agency. https://www.housingagency.ie/publications/apartment-living-ireland-2019
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The Housing Agency (2021). Housing experience, attitudes and aspirations of Irish Apartment Residents, 2019 [dataset]. Version 1. Dublin: Irish Social Science Data Archive SN: 0072-02 https://www.ucd.ie/issda/data/housingexperienceattitudesandaspirationsofirishhouseholds/irishhousingexperiences2019/
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