Changes to the collection of short walk data in the NTS Glenn Goodman, DfT

A walk less than one mile but greater than 50 yards in distance. What is a short walk?

Timeline Develop weighting Short walks experiment Further experiment Public consultation Consultation response Cognitive testing Decision on method October 2015

Background: Household survey of personal travel First survey in Continuous since : n = 7k households, 16k people (63% resp. rate) Complex design – stratified two-stage random sample

Data collection

Travel week allocation Day 1 = Monday? Day 7 = Sunday? Respondents allocated start day – uniform spread across week and month

Data collection

The importance of the data Walking & cycling policy Transport forecasts and models

The decline of walking 234 trips 133 trips 58 trips 70 trips

Research outline Data are weighted to account for under- reporting – short walks only collected on day 7

Weighting for under-reporting

Research question Data are weighted to account for under- reporting – short walks only collected on day 7 Aims: To assess whether under-reporting of short walk trips exists If so, correct this under-reporting

Timeline Short walks experiment April – June 2013

Experiment outline Aim: To assess day 1 vs. day 7 Sample size: 1,000 Designed to detect a 5% point change £££

2013 short walks experiment

Under-reporting: adults

Under-reporting: children 11% 1.5%

Under-reporting: type of walk A B Short walk only trip AB Multi stage trip

Under-reporting: type of walk 1.1%

Timeline Short walks experiment April – June 2013 Public consultation July – Sept 2014

Consultation options 1 2 Day 7 Another experiment Produce weight 53 4 Day 1 Produce weight Break in series

Timeline Public consultation July – Sept 2014 Consultation response December 2014

Consultation response “…I would want to be very sure before making irreversible modifications to NTS protocols…the NTS has weaknesses and biases that are essentially stationary…turbulent biases are much worse…” 34 Day 1

Timeline Consultation response December 2014 Develop weighting Ongoing

The approach to weighting Short walk only trips by adults Logistic regression to calculate likelihoods Determine explanatory variables Produce weights

Developing back-series weight Age Economic status Car access

Example – car access 16% 7%

Developing back-series weight Age Economic status Car access Gender – not significant

Example – gender

Developing back-series weight Age Economic status Car access Gender Household region Settlement type (urban/rural) Mobility Income – not significant – excluded

Developing back-series weight Age + economic status  0-16  Full time  Part-time  Retired  Other non-work Car access  Main driver  Other driver  Non-driver  No access

Logistic regression: Day 7

Logistic regression: Day 1

Relative likelihoods

Day 7 weighted Applying the weights Day 7 unweighted Day 1

Applying the weights

Historic likelihoods Age 0-16 Adult, full-time Adult, part-time Adult, other non-work Retired

Further work Cognitive interviews Comparisons with other studies  London Travel Demand Survey  Scottish Household Survey Further experiment

Timeline Develop weighting Short walks experiment Further experiment Public consultation Consultation response Cognitive testing Decision on method October 2015

Conclusion Experience of formal consultation process Highlights the value of ONS Methodology Advisory Service Lessons for other household surveys Better data on walking for the future!