Key issues for longitudinal research design:

The challenges of longitudinal research “The success of a longitudinal study depends on stable leadership from a committed principal investigator and a team of highly skilled researchers”
(Bynner et al, 2006) Sample Data collection Duration
(& relevance) Ethics Cost Data analysis<br>

The Sample Two main issues:
Sample design
Non-response and attrition<br>

Sample design considerations What is the population of interest?
All vulnerable children?
Sub-groups of interest? E.g. with particular characteristics – age, family circumstances, area where they live, interventions received
What do you want to be able to say about them?
Use sample to generalise to population?
Compare outcomes and experiences between children in different groups?
How will you find/recruit them?
Is there a sampling frame with the info you need?
Will you need the help of an agency/organisation to recruit?<br>

Sampling precision (1) When using a sample, the data produces ‘estimates’ of what the real value may be in the population. The precision of these estimates is affected by:
Sample size
Sample clustering
Measuring sample precision:
Use ‘confidence intervals’ and ‘standard errors’
Confidence interval (CI)
Typically 95% meaning 95 times out of 100 this interval will capture the true population value that we are trying to estimate
Expressed as e.g. 64% (+/- 6%) suggesting the true value is somewhere between 58% and 70%
Differences will usually have to be of the magnitude of the CI for it to be statistically significant – e.g. in example above, an increase or decrease of around 6% would be necessary.
Smaller sample sizes produce larger CIs requiring greater change for statistically significant differences to be detected<br>

Sampling precision (2) Sample numbers required in each group to demonstrate significant differences (with a power of 0.8)<br>

GUS response and attrition rates<br>

GUS: Sweep 5 response by age of mother<br>

Non-contact and refusal rates<br>

Sample maintenance strategies Keeping in touch
Tracing
Keeping respondents informed
Valuing and appreciating respondents (including, but not restricted to, use of incentives)
Boosts of key sub-groups of interest and on-going sample refreshment
Making reasonable demands<br>

Sample maintenance: keeping in touch Potentially willing respondents can be lost by virtue of moving home.
Important to establish effective procedures for obtaining updated contact information.
Techniques include:
Collecting as much contact information as possible at first contact including telephone/mobile numbers and e-mail
Information about ‘stable contacts’ – someone who knows the respondent and would know where they had moved to
Regular mailings with return address – undelivered items act as address checks ahead of fieldwork
Updates from administrative and service databases<br>

Sample maintenance: keeping respondents informed In any research project, it is considered important to provide good information to respondents about the purpose and nature of research
Respondents must understand the longitudinal nature of the study so that they also recognise why they are repeatedly visited and why they are irreplaceable
Many studies adopt a ‘branding’ approach – a name and logo that clearly identifies the study and which is easily recognisable by respondents
Websites can be extremely useful in providing more detailed information<br>

Sample maintenance: valuing and appreciating respondents If respondents are going to continue to take part in a longitudinal study they need to feel that their time and effort is valued and is worthwhile.
This can be demonstrated through:
The interviewer
Thank you letters sent after each interview
Providing evidence that survey findings have been used
Illustrating the impact they have had on government policy
Use of incentives
Non-financial rewards – gifts such as pens, fridge magnets, calendars<br>

Being part of NCDS There’s one thing I’m guaranteed, all of my entire life, is one birthday card.
I’ve always liked being part of it, I’ve always enjoyed being part of it because it’s different and I’m quite proud of it really.
I think I could almost put this in as a landmark in my life.
I haven’t kidded on about anything in my life, warts and all, I’ve been honest and I’ve said it all.
….. I think, you know, it does make you feel special in certain ways, like really…..
I haven’t ever seen anything negative in it actually, not anything negative at all…..I’ve always felt comfortable and I always know that if I don’t want to answer a question I don’t have to………… I think it’s just been fascinating<br>

Recognising the importance of NCDS I can remember becoming part of the NCDS, I didn’t understand it.... I think I’ve just grown to understand it more as I’ve got older and the importance of it and how it’s helping everybody really, that’s what I think.
Well, I think to a certain extent you’ve got to say it’s mainly for helping others, you know. Like you say it’s no benefit to me to do it, but then again it’s no skin off my nose not to do it, so. It’s one of those things like, you know….I don’t see a reason [not to]……
I think it’s interesting that they’re actually following all these people, right through their life and ……they find out comparisons. Aye, I think it’s really…. that’s why I take the bother to, aye, come. I want to be part of it because I’ve been in it all my life.<br>

Data collection: what to ask and when Decisions on content of data collection require good planning – important to ask the right questions at the right time
Take a ‘longitudinal’ view:
What ‘stage’ are your subjects at?
What stage will they reach?
What situations, characteristics or contexts might you want to compare between those two stages?
What might be significant at stage 1 when you are comparing outcomes at later stages?
Decisions on content will usually be theory or hypothesis-based
What if you miss something?<br>

Data collection: intervals between fieldwork How often do you follow-up your sample? This is dependent upon:
Respondent burden
Developmental stages, processes or transitions that you are interested in
Budget
There is no recognised nor legitimate pattern – it’s largely dependent upon the objectives and focus of the research<br>

Follow-up intervals of selected UK child cohort studies<br>

GUS: Sources of data<br>

Data analysis Benefits of longitudinal data
Measuring change over time:
Flows into and out of ‘states’ (e.g. poverty, unemployment, being looked after)
The effects of change, or of state durations, on outcomes
Impact of interventions
‘Individual’ development
Temporal ordering of events
Improved control for omitted explanatory variables
Improved control for the effects of previous states
Exploring the effects of ageing and cohort membership<br>

Data analysis Drawbacks of longitudinal data
Data management
Complex structure/relations
Complex variable/samples
Resultant file and variable management requires training and skills of good practice
Software issues
Complexity of methods
Some methods only available via specific software packages<br>

Longitudinal models Two main modelling approaches in social science research:
Event history analysis, time to an event
(Also known as: duration analysis; survival analysis; failure time; duration economics; hazard modelling)
Panel data analysis
Regression models suitable for repeated observations
Time generally conceptualised as being discrete
Extension of standard regression models
Closely related to multilevel modelling
(Simple methods can also be used)<br>

Ethical issues (1) Confidentiality, data security and data access
Safeguarding confidentiality through
Restricting the data that are released
Controlling the arrangements under which potentially disclosive data is released
Data access/release
Providing data for researchers to analyse on their desktop with the level of sensitive detail restricted
Providing more sensitive data under a special licence
Remote access where raw data is never released and analyses are run in house on behalf of researchers who receive edited outputs
Safe settings where researchers are required to visit a protected site where access to the data is carefully managed.<br>

Ethical issues (2) Informed consent
What is ‘informed consent’?
Respondents must understand that the project is longitudinal in nature and what that means for them
They are free to withdraw at any time from the project as a whole or any aspect of it
One-off or repeated consent?
No universal practice, but
Some form of repeated consent would normally be involved<br>

Summary Longitudinal research in any methodological discipline presents a set of core challenges
The key issue is to consider, in detail, how the fundamental temporal nature of the project affects the basic aspects of its design including:
The sample
Data collection
Data analysis
Ethics
Requires a more complex design, but a good design will produce tremendously valuable data<br>