1. Section 2: Types of longitudinal studies
From the CLOSER Learning Hub
Module: Introduction to longitudinal studies

2. Panel studies
Follow the same individuals over time and vary considerably in scope and scale
Household panel studies collect information from the whole household, rather than individuals
Household panels incorporate new participants as households break-up and reform
Panel studies follow the same individuals over time and vary considerably in scope and scale. Examples include online opinion panels (which invite members of the public to sign up and then complete regular surveys) and short-term studies whereby people are followed up once or twice after an initial interview.
Some of the most complex panel studies are household panel surveys. Rather than only collecting data from one person (as tends to happen with cohort studies or simpler panel studies), information is normally collected about the whole household at each wave. These studies aim to remain representative of the population of households as a whole, so these surveys need to ensure that they can include new entrants, persons and families into the population. Understanding Society is an example of a household panel survey.

3. Cohort studies
Follow groups of individuals with specific temporal boundaries
Birth cohort studies which follow groups of people born within the same time period
Cohort studies represent a particular cohort of people, rather than the population as a whole
Cohort studies are concerned with charting the lives of groups of individuals who experience the same life events within a given time period. The most well-known examples are birth cohort studies which follow groups of people born within the same time period (for example, later on you’ll hear about the UK birth cohort surveys that randomly sampled from all children born in a particular week). Examples of non-birth cohorts include students leaving university at a particular point or new recruits entering a particular organisation or industry.
It is important to remember that birth cohort studies represent a particular cohort of people, rather than the population as a whole. However, comparing different birth cohorts allows researchers to understand how and why society is changing.

4. Record linkage studies
Conducted without personal interviews by linking administrative records (for example, benefit receipts or census records) for the same individuals over time
Advantages: potentially large sample sizes, less risk of participant drop out or reporting error
Disadvantages: limited by the nature of the records they are based on
Example: UK Census Longitudinal Studies
Record linkage studies can be conducted without personal interviews by linking administrative records (for example, benefit receipts or census records) for the same individuals over time. The advantages of using these types of longitudinal data are the potentially enormous sample sizes, which mean detailed analyses can be constructed for whole populations. By not having to conduct interviews, there is less risk of respondent dropout or reporting errors.
For example, there are three UK census-based longitudinal studies, which link census and life event data for a sample of the population of the UK population.
However, the scope for using these types of study is limited by the nature of the records they are based on, which is unlikely to cover the range of areas of interest to researchers. It may also be difficult or impossible to use record linkage data because of concerns about confidentiality or privacy restrictions.

5. Prospective vs retrospective studies
Prospective studies collect data about their participants as their characteristics or circumstances change.
Example: British birth cohort studies
Retrospective studies collect information about participants’ pasts, either through recall questions or linking historic records.
Example: Hertfordshire Cohort Study
Another key distinction in longitudinal research is between prospective and retrospective studies:
In prospective studies, individuals are followed over time and data about them is collected as their characteristics or circumstances change. Birth cohort studies are a good example of prospective studies.
In retrospective studies, individuals are sampled and information is collected about their past. This might be through interviews in which participants are asked to recall important events, or by identifying relevant administrative data to fill in information on past events and circumstances. In the case of historical cohort studies, people are linked to existing historical information. The Hertfordshire Cohort Study is an example of an historical cohort study.
In reality, many studies use both prospective and retrospective methods. For example, because birth cohort studies interview their participants every few years or so, participants are often asked to retrospectively provide information on their lives since the previous interview (for example, ‘since we last saw you, have you been diagnosed with any of the following medical conditions?’). Meanwhile, household panel studies, which may start interviewing participants in adulthood, often collect an array of retrospective information about past events.

6. Longitudinal vs cross-sectional studies
One point in time
Several points in time
Different samples
Same sample
Snapshot of a given point in time, change at a societal level
Change at the individual level
Ex. British Social Attitudes Survey, Labour Force Survey
Ex. British Birth Cohort Studies, Understanding Society
Longitudinal studies differ from one-off, or cross-sectional, studies. The main difference is that cross-sectional studies interview a fresh sample of people each time they are carried out, whereas longitudinal studies follow the same sample of people over time.
Some cross-sectional studies take place regularly, each time including a large number of repeat questions. For example, the British Social Attitudes Survey is a repeat cross-sectional study that has been carried out nearly every year since It provides excellent data about how Britain’s attitudes and values have changed (or not changed) over time.
Repeating the same questions in each round allows researchers to look at how society as a whole has changed over time. But because the questions are asked of a new sample every time, these studies can only reveal change at an aggregate level – they can shed little light on who has changed, or how or why.
For example, the 2015 British Social Attitudes survey found that 66 per cent of people thought that “it’s everybody’s duty to vote” in a general election. This is up from 57 per cent from Sixty-one per cent of people felt it was everyone’s duty to vote when the survey was carried out in 2010, immediately after the last general election.
What do these findings tell us? The data clearly show us that, overall, fewer people now than in the mid-1990s think that citizens have a duty to vote. We can look at the characteristics of those who do or don’t agree with this view, and how the profile of these groups had changed over time. We can also examine how the likelihood of thinking that voting is a duty has changed among different population groups (for example, different age groups or ethnicities).
These sorts of calculations would provide some very helpful insights. But there are many things that this kind of cross-sectional data cannot tell us, but which longitudinal data would help us to address. For example:
Which individuals changed their views about voting over the period? What are their characteristics? Do some people switch, and then switch back again?
The British Social Attitudes findings show us the net or aggregate change over time – the difference between the proportion who thought voting was a duty in 1994 and the equivalent proportion now. But this tells us nothing about change at an individual level, or gross For example, what proportion became more inclined to think voting is a duty and what proportion became less inclined? It is important to bear in mind that if these two proportions are similar, they could cancel one another out at a net level and make it appear that very little has changed over all, even though substantial numbers of people have changed their views.
What factors best explain the transition away from thinking voting is a duty?
Sometimes data from longitudinal studies is analysed cross-sectionally. This means that the researcher is just focusing on the information collected at one round of the study, and not linking that information to data from earlier or later rounds.