Accredited official statistics

Chapter 2 Sample selection

Published 27 August 2025

Applies to England

Sample size and structure

The NTS 2024 was designed to provide a representative sample of households in England and was based on a stratified 2-stage random probability sample of private households. The sampling frame was the ‘small user’ Postcode Address File (PAF), a list of all addresses in the country (also known as delivery points).

The sample for the 2024 survey was drawn firstly by selecting the Primary Sampling Units (PSUs), and then by selecting addresses within PSUs. The sample design employs postcode sectors as PSUs. Each PSU represents one sample point (also known as an assignment), and for fieldwork purposes each point is issued to an individual interviewer.

For NTS 2024, the same sample size was drawn as NTS 2023. 1,164 PSUs were selected. 22 addresses from each PSU, equating to a total of 25,608 selected addresses.

Quasi-panel design

Following a review of the NTS methodology in 2000, it was decided that the NTS should introduce a quasi-panel design from 2002 onwards. According to this design, half the PSUs in a given year’s sample are retained for the next year’s sample and the other half are replaced. This has the effect of reducing the variance of estimates of year-on-year change.

Therefore 582 of the PSUs selected for the 2023 sample were retained for the 2024 core sample. These 582 retained PSUs were supplemented with 582 new PSUs. The PSUs carried over from the 2023 sample for inclusion in 2024 were excluded from the 2024 sample frame, so they could not appear twice in the sample, however, the dropped PSUs from 2023 were included.

Whilst the same PSU postcode sectors might appear in different survey years, no single addresses were allowed to be included in 3 consecutive years to minimise the chances of the same address being selected again. Each year, NatCen provides the sampling company with a list of the addresses selected for the previous 3 survey years. These addresses were excluded from the sampling frame before the addresses for 2024 were selected. This means respondents to the 3 previous year’s surveys in the carried over PSUs could not be contacted again.

For further information about the methodological review, see Elliott, D. (2000) ONS Quality Review of the National Travel Survey: Some Aspects of Design and Estimation Methods.

Selection of sample points

Sample points were selected firstly by generating a list of all postcode sectors in England (excluding those in the Isles of Scilly due to cost of interviewing). Sectors carried over from the previous year were also excluded, as described in section 2.2 above. Sectors with fewer than 500 delivery points were grouped with an adjacent sector. Grouped sectors were then treated as one PSU. On average each PSU contained about 3,250 delivery points.

This list of grouped postcode sectors in England was then stratified using a regional variable, an urban or rural indicator, a car ownership indicator. NTS 2023 also used a working from home indicator as the fourth stratifier. This was done to increase the precision of the sample and to ensure that the different strata in the population are correctly represented. Random samples of PSUs were then selected within each stratum. This stratification approach was first implemented in NTS 2015 following a stratification review that NatCen carried out in 2014. NTS 2024 sampling used newly released Census 2021 data for stratification, rather than Census 2011. As the 2021 Census took place during COVID-19 lockdown restrictions, the measure of working from home differed substantially from 2011. Given the temporary restrictions during the census, the 2021 variable was judged not to be an accurate measure of ongoing working at home levels. As a precaution, it was therefore removed from the stratification of the NTS 2024 sample. The third stratification variable, proportion of households with no car, was used in continuous rather than percentile form instead. Comparison of 2011 and 2021 census data confirmed that this variable was not impacted by lockdown restrictions.

The regional strata for England are based on the International Territorial Level 2 (ITL2) areas, formerly NUTS 2, grouped in a few cases where single areas are too small. International Territorial Levels (formerly known as Nomenclature of Units for Territorial Statistics) replaces the European-wide geographical classification developed by the European Office for Statistics (Eurostat) following the UK withdrawal from the EU. The 2 classifications are equivalent, and the categories unchanged from previous years. ITL2 roughly relates to counties or groups of counties in England. The 30 regional strata for the survey are shown in Table 2.1, along with the region codes that each of the strata belong to.

Table 2.1: NTS regional stratification variable

Stratification number	England	Region code
1	Inner London – East	7 Greater London
2	Inner London – West	7 Greater London
3	Outer London – East and North East	7 Greater London
4	Outer London – South	7 Greater London
5	Outer London West and North West	7 Greater London
6	Devon and Cornwall	9 South West
7	North Somerset, North East Somerset, Bath, Somerset and Dorset	9 South West
8	Bristol, South Gloucestershire, Gloucestershire and Wiltshire	9 South West
9	Oxfordshire, Buckinghamshire and Berkshire	8 South East
10	Hampshire and Isle of Wight	8 South East
11	Kent	8 South East
12	West Sussex and East Sussex	8 South East
13	Surrey	8 South East
14	Essex	6 Eastern
15	Cambridgeshire, Suffolk and Norfolk	6 Eastern
16	Hertfordshire and Bedfordshire	6 Eastern
17	Leicestershire, Lincolnshire and Northamptonshire	4 East Midlands
18	Warwickshire and Hereford and Worcester	5 West Midlands
19	West Midlands	5 West Midlands
20	Shropshire and Staffordshire	5 West Midlands
21	Nottinghamshire and Derbyshire	4 East Midlands
22	Cheshire	2 North West and Merseyside
23	Merseyside	2 North West and Merseyside
24	Greater Manchester	2 North West and Merseyside
25	Lancashire and Cumbria	2 North West and Merseyside
26	South Yorkshire	3 Yorkshire and Humberside
27	West Yorkshire	3 Yorkshire and Humberside
28	North Yorkshire and Humberside	3 Yorkshire and Humberside
29	Cleveland, County Durham and Northumberland	1 North East
30	Tyne and Wear	1 North East

Within each region, postcode sectors were allocated to “urban” or “rural” based on the urban or rural indicator creating 51 “expanded” regions. The urban rural indicator itself was based on the 2021 Census and derived from the 6-category Rural Urban Classification. Within each “expanded” region, postcode sectors were listed in increasing order of the proportion of households with no car (according to the 2021 Census).

In the next step of the process, 582 postcode sectors were then systematically selected for the core sample with probability proportional to delivery point count. Differential sampling fractions were used in Inner London, Outer London and the rest of England in order to oversample London (see section 2.4 for further details). These sectors were then added to the 582 sectors carried over from the previous year’s survey to produce the initial core sample of 1,164 sectors.

Oversampling of London

Each year, London PSUs are oversampled. Response rates tend to be much lower in London compared with the rest of England, with rates being lowest in Inner London. The NTS oversamples Inner and Outer London with the aim of achieving responding sample sizes in London and elsewhere which are proportional to their population. Estimates of response rates were made to oversample Inner and Outer London based on recent years of NTS. Of the 1,164 PSUs in the sample drawn, 113 were in Outer London and 82 in Inner London.

Selection of addresses

The number of addresses drawn per PSU increased from 17 to 22 for NTS 2023. The aim of this increase in point size was to achieve a larger responding sample without a proportionate increase in fieldwork costs. The clustering effect of this increased point size was tested in a 2013 split sample experiment and found to be acceptable. As a result, 22 addresses were systematically selected from each of the 1,164 PSUs that were drawn for 2024, a total of 25,608 selected addresses.

Self-completion section

Starting in NTS 2017, a Computer Assisted Self Interviewing (CASI) module for transport satisfaction questions was added, where one adult from those present during the household interview is asked to complete the satisfaction questions.

Introduction of the CASI module added a new element to the sample design, requiring one individual to be randomly selected per household. The methodology for incorporating the CASI module into the NTS sample was based on the methodological development work that NatCen carried out in 2016. This methodology is detailed in Appendix Q1 of the NTS 2017 Technical Report.

This development work showed that inclusion of the satisfaction questions in this way requires the selection of one adult per household among those present during the interview. Selecting only from those present, however, introduces a non-random element in the sampling process, as some individuals (those who are absent) would have a zero probability of selection, thus introducing bias to the selected sample.

The development work also showed that younger men and women are under-represented in the sub-sample of NTS household members who are present during the interview. Given that younger people are less likely to live alone, this under-representation is likely to increase if one person per household is selected at random amongst those who are present. Consequently the development work recommended varying the probabilities of selection so that the number of young men and women selected is increased. The CASI sample for NTS 2024 was therefore recruited using an equal probability of selection, except in households where both people aged 16 to 29 and 30 or over were present. In such households, those aged 16 to 29 were selected with an 80% probability. This differential selection probability was then adjusted for in the weighting of the CASI responding sample.

Allocation of PSUs to months

To allocate PSUs evenly across NTS 2024, the survey year was divided into 12 quota (fieldwork) months and equal numbers of PSUs (291) were initially assigned to each quarter, resulting in an average of 97 points being issued each month.

Allocating PSUs evenly across a quarter (rather than a month) results in a more even spread of the average number of points and hence interviews and travel diaries per day across months. This approach makes it easier to control for variation across seasons. Furthermore, PSUs were allocated to quota months such that a nationally representative sample would be obtained for each quarter. Until 2016, an equal number of PSUs were issued each month, which meant that shorter months, particularly February, were slightly overrepresented in the data.

As noted in section 2.3 above, random samples of PSUs were selected within each stratum, as well as being evenly spread across each quarter. The distribution of sample points for each quota month across the major regional strata is shown in Appendix K.

Fieldwork start dates

Since 2014, an additional process followed the selection of sample points. As part of this process, start dates are evenly spread across each month and then assigned to the points per month at random to provide an even spread of responses across the year.

Prior to 2014, interviewers were instructed to begin fieldwork at the start of the quota month. Additionally, travel week start dates were allocated within quota months, which ran mid-month to mid-month. However, analysis using 2012 data showed that this design led to an uneven spread of travel week start dates across the month due to interviewers following similar fieldwork patterns. In 2014 a new design was implemented to address this issue, whereby interviewers were assigned to start fieldwork on different dates across the month to ensure that the interviewing dates were more evenly spread.

Selection of households at sampled addresses

Interviewers should interview only one household per address given to them in their sample point. At some addresses, interviewers may find that more than one household is present. A household is defined as one person or a group of people living in a dwelling unit, who (a) share cooking facilities and (b) share a living room, sitting room or a dining area.

A single address may also contain more than one dwelling unit, for example a house which has been split into 2 flats. A dwelling unit is a living space with its own front door, which can be either a street door or a door within a house or block of flats. Moreover, a single dwelling unit may include just one household or multiple resident households, for example 2 families living as 2 separate households in one house.

In England, addresses containing multiple dwelling units are not identified in the PAF and will not be detected until the interviewer has visited the address. For example, most apartments, whether in a block of flats or within a house, will be listed in their own right in the PAF. That is, these apartments are listed with their own address in the PAF, and assuming they meet the criteria of a single address (as defined above) they would be considered as one dwelling unit only. However, for some apartment blocks or houses that contain multiple dwelling units, the PAF will not list the individual addresses for each dwelling unit. Where this is the case, the interviewer will need to establish the different dwelling units that are part of the address that was given to them in their sample point. Furthermore, the PAF does not provide information on the number of households at a given address, and so the presence of other dwelling units is only detected when the interviewer visits the address.

Households residing at PAF-sampled addresses with multiple dwelling units or households, or both, will have had a lower chance of selection than others. While there are relatively few such addresses (1%), they account for a larger proportion of households, and these households tend to be rather different to others (poorer, younger, and smaller), so consequent biases may not be entirely trivial.

Interviewers must select one household to approach to take part at each sampled address. Interviewers are instructed to first establish the number of dwelling units at each sampled address. If there is more than one dwelling unit at the address, interviewers list these dwelling units in the electronic Address Record Form system (eARF) on their laptops so that the computer can randomly sample one of them. They then establish the number of households residing within the dwelling unit (whether it is the only dwelling unit at the address or the selected dwelling unit at an address with multiple dwelling units). Similarly, if there is more than one household, interviewers list them out in the eARF so that the computer can randomly select one of them.

Corrective weighting is then used to remove any bias arising from the lower chance of selection among dwelling units or households residing at multi-household addresses.

Ineligible (deadwood) addresses

The following types of address were classified as ineligible in 2024:

• houses not yet built or under construction

• demolished or derelict buildings or buildings where the address has “disappeared” when 2 addresses were combined into one

• vacant or empty housing unit: housing units known not to contain any resident household on the date of the first contact attempt

• a non-residential address: an address occupied solely by a business, school, government office or other organisation with no resident persons

• residential accommodation not used as the main residence of any of the residents. This is likely to apply to second homes, seasonal, vacation or temporary residences, and these were excluded to avoid double counting

• a communal establishment or institution: that is, an address at which 4 or more unrelated people sleep; while they may or may not eat communally, the establishment must be run or managed by the owner or a person (or persons) employed for this purpose

• an address is residential and occupied by a private household(s), but does not contain any household eligible for the survey; it is very rare for a residential household not to be eligible for the NTS interview, exceptions include ‘Household of foreign diplomat or foreign serviceman living on a base’, addresses which are not the ‘Main residence’ of any of the residents and addresses where there are no residents aged 16 or over

• an address out of sample: that is, cases where interviewers were directed not to approach a particular address; this is very rare and usually only occurs where an address should not have been listed on the original sampling frame

For further information about outcome coding, see section 3.14.

PSU-level variables

In addition to the information provided by members of the sampled households, the NTS also collects information measured at the PSU-level. The value of a PSU-level variable applies to all households living within that PSU. The PSU-level is therefore the highest level at which the data may be analysed, coming just above the Household level in the analysis hierarchy.