Variable Description
Family type classifies family nuclei according to the presence or absence of couples, parents, and children.
en-NZFollowing a detailed investigation into potential quality concerns the quality rating of this variable has been changed from very poor quality to moderate quality.
Families and households in the 2018 Census: Data sources, family coding, and data quality has detailed information on the quality assessment for these variables and some changes in our methodology.
Priority level
Priority level 2
We assign a priority level to all census variables: Priority 1, 2, or 3 (with 1 being highest and 3 being the lowest priority).
Family type is a priority 2 variable. Priority 2 variables cover key subject populations that are important for policy development, evaluation, or monitoring. These variables are given second priority in terms of quality, time, and resources across all phases of a census.
The census priority level for family type remains the same as 2013.
Quality Management Strategy and the Information by variable for family type (2013) have more information on the priority rating.
Overall quality rating for 2018 Census
Moderate quality
Data quality processes section below has more detail on the rating for this variable.
Subject population
Families in occupied private dwellings
‘Subject population’ means the people, families, households, or dwellings to whom the variable applies.
How this data is classified
Family Type - New Zealand Standard Classification 1999 V1.0.0
Family type is a flat classification.
1 Couple Without Children
2 Couple With Child(ren)
3 One Parent With Child(ren)
To be a 'child in a family nucleus', a person must usually reside with at least one parent, and have no partner or child(ren) of their own living in the same household.
Note that 'child in a family nucleus' can apply to a person of any age.
The Standards and Classifications page provides background information on classifications and standards.
Question format
Family type is derived from information about all the people who usually live in the household: residents who are present on census night and residents who are absent on census night (absentees). The following variables are used to determine relationships between the usual residents of the household:
- Relationship to reference person
- Absentee relationship to reference person
- Living arrangements
For online forms the household set-up form asks for residents present on census night, any absentees, and the relationship of each resident to the reference person. Living arrangements is asked on the individual form.
On paper forms the dwelling form asks for residents present on census night and their relationship to reference person (question 17). Any absentees are listed on the dwelling form with absentee relationship to reference person (question 20). Living arrangements is asked on the individual form (question 17).
Both forms collect further information about absentees (usual residents who are absent on census night) regarding whether they are in New Zealand or overseas, and whether they are away for less than 12 months or 12 months or more. Absentees away from New Zealand for 12 months or more are not included as usual residents of the household.
Stats NZ Store House has samples for both the individual and dwelling paper forms.
How this data is used
Outside Stats NZ
- By central government agencies, local authorities, private organisations, and researchers in the formulation of social policy, for planning and monitoring programmes, and for research purposes.
Within Stats NZ
- To derive household and family projections.
2018 data sources
We used alternative data sources for missing census responses and responses that could not be classified or did not provide the type of information asked for. Where possible, we used administrative data from the Integrated Data Infrastructure (IDI).
The table below shows the breakdown of the various data sources used to place people in households (used to derive family type).
| 2018 sources used to derive family type – households in occupied private dwellings |
|
|---|---|
| Source | Percent |
| Response from 2018 Census | 93.4 percent |
| Response from 2018 Census and administrative data* | 0.8 percent |
| Administrative data | 2.2 percent |
| No information | 3.6 percent |
| Total | 100 percent |
| Due to rounding, individual figures may not always sum to the stated total(s) *Households where some members were enumerated from 2018 Census forms, and others from administrative data. |
‘No information’ in the table above is the percentage of non-responding households. A household is classified as non-responding when we have evidence that a private dwelling was occupied on census night but we did not receive a response and we were unable to identify usual residents of the household in administrative data. The usual residents of these non-responding dwellings may have been present in administrative data, but we did not have enough evidence to place them into a specific household. In these cases, individuals were placed into a meshblock instead. Non-responding households were coded to ‘household composition unidentifiable’.
Administrative data sources
We enumerated individuals from the range of sources available in the Integrated Data Infrastructure (IDI).
The potential for linked administrative data to provide household and family information provides information on sources of administrative data used.
Overview of statistical methods for adding admin records to the 2018 Census dataset provides information on the linking of census responses to the IDI and has more information on the timeliness of administrative data.
Please note that when examining family type data for specific population groups within the subject population, the percentage that is from administrative data may differ from that for the overall subject population.
Missing and residual responses
Family type does not have a non-response or ‘not stated’ category. ‘No information’ in the data sources table is the percentage of households we were unable to determine household composition for, and therefore were unable to identify if the household contains a family.
Family type does not have a ‘family type unidentifiable category’ as the process for determining whether a household contains a family also determines the family type.
Data quality processes
Overall quality rating: Moderate quality
Data was evaluated to assess whether it meets quality standards and is suitable for use.
Three quality metrics contributed to the overall quality rating:
- data sources and coverage
- consistency and coherence
- data quality.
The lowest rated metric determines the overall quality rating.
Data quality assurance for 2018 Census provides more information on the quality rating scale.
Data sources and coverage: High quality
We have assessed the quality of all the data sources that contribute to the output for the variable. To calculate a data sources and coverage quality score for a variable, each data source is rated and multiplied by the proportion it contributes to the total output.
The rating for a valid census response is defined as 1.00. Ratings for other sources are the best estimates available of their quality relative to a census response. Each source that contributes to the output for that variable is then multiplied by the proportion it contributes to the total output. The total score then determines the metric rating according to the following range:
- 98–100 = very high
- 95–<98 = high
- 90–<95 = moderate
- 75–<90 = poor
- <75 = very poor.
The data sources and coverage quality rating for family type is the same as for household composition, as family type is derived from household composition. For household composition, the data source ratings represent the likelihood that the correct people are placed within the correct household.
The proportion of data from 2018 Census and admin data contributed to the score of 0.96, determining the high quality rating.
| Quality rating calculation table for the sources used to derive family type – 2018 households in occupied private dwellings | |||
|---|---|---|---|
| Source | Rating | Percent of total | Score contribution |
| 2018 Census form | 1.00 | 93.39 | 0.93 |
| 2018 Census and admin data* | 1.00 | 0.82 | 0.01 |
| Admin data | 0.64 | 2.16 | 0.01 |
| No Information | 0.00 | 3.63 | 0.00 |
| Total | 100.00 | 0.96 | |
| Due to rounding, individual figures may not always sum to the stated total(s) or score contributions. *Households where some members were enumerated from 2018 Census forms, and others from administrative data. |
Consistency and coherence: High quality
Family type data is consistent with expectations across nearly all consistency checks, with some minor variation from expectations or benchmarks that makes sense due to real-world change, incorporation of other sources of data, or a change in how the variable has been collected.
Data quality: Moderate quality
Data quality was determined by assessing how many records in the subject population had been flagged as having a potential error. An error flag indicates a household may have been miscoded or may have a missing person, and therefore may have incorrect characteristics.
Family and household variables with error flag rates below 6 percent were given a data quality rating of moderate, those with between 6 percent and 9.99 percent were given a rating of poor, while variables with error flag rates of 10 percent or greater were given a rating of very poor.
Families in occupied private dwellings had an error flag rate of less than 6 percent, determining the moderate quality rating for the family type variable.
Families and households in the 2018 Census: Data sources, family coding, and data quality has more information on error flags.
Quality ratings of related variables
The table below summarises the quality ratings of variables related to family type.
| Quality ratings of related variables | ||||
|---|---|---|---|---|
| Variable | Data sources and coverage | Consistency and coherence | Data quality | Overall quality rating |
| Count of families | High | Very high | Moderate | Moderate |
| Count of people in families | Moderate | High | Moderate | Moderate |
| Family type by number of children | High | High | Moderate | Moderate |
| Family type by child dependency status | High | High | Moderate | Moderate |
| Family type with type of couple | High | Very poor | Moderate | Very poor |
| Number of people in family | High | High | Moderate | Moderate |
| Number of children in family | High | High | Moderate | Moderate |
| Number of dependent children in family | High | High | Moderate | Moderate |
| Number of adult children in family | High | High | Moderate | Moderate |
| Age of youngest child in family | High | High | Moderate | Moderate |
| Age of youngest dependent child in family | High | High | Moderate | Moderate |
| Type of couple | High | Very poor | Moderate | Very poor |
| Age of male partner in opposite-sex couple | High | Moderate | Moderate | Moderate |
| Age of female partner in opposite-sex couple | High | Moderate | Moderate | Moderate |
| Age of older partner in same-sex couple | High | Very poor | Poor | Very poor |
| Age of younger partner in same-sex couple | High | Very poor | Poor | Very poor |
| Sex of sole parent | High | High | Moderate | Moderate |
| Identification of individual’s family nucleus | Moderate | High | Moderate | Moderate |
| Individual’s role in family nucleus | Moderate | Moderate | Moderate | Moderate |
| Dependent child under 18 indicator | Moderate | High | Moderate | Moderate |
| Dependent young person indicator | Moderate | High | Moderate | Moderate |
Quality issues to note for related variables:
- Families and households in the 2018 Census: Data sources, family coding, and data quality has information on the quality assessment for these variables.
Recommendations for use and further information
The overall quality of family type data is moderate and comparable with 2006 and 2013 data.
When using this data you should be aware that:
- data has been assessed to be consistent at the regional council level of geography. Some variation is possible at geographies below this level.
- new methodology has been used to assess the data sources and coverage, and data quality metrics. Families and households in the 2018 Census: Data sources, family coding, and data quality has further information on the quality assessment methodology for this variable.
Contact our Information Centre for further information about using this variable
Representation
Concept
Family
en-NZ
Families and households
en-NZ
