Longitudinal studies (cohort/panel studies) |
1. Single sample over extended period of time.
2. Enables the same individuals to be compared over time (diachronic analysis).
3. Micro-level analysis. |
1. Useful for establishing causal relationships and for making reliable inferences.
2. Shows how changing properties of individuals fit into systemic change.
3. Operates within the known limits of instrumentation employed.
4. Separates real trends from chance occurrence.
5. Brings the benefits of extended time frames.
6. Useful for charting growth and development.
7. Gathers data contemporaneously rather than retrospectively, thereby avoiding the problems of selective or false memory.
8. Economical in that a picture of the sample is built up over time.
9. In-depth and comprehensive coverage of a wide range of variables, both initial and emergent – individual specific effects and population heterogeneity.
10. Enables change to be analyzed at the individual/micro level.
11. Enables the dynamics of change to be caught, the flows into and out of particular states and the transitions between states.
12. Individual level data are more accurate than macro-level, cross-sectional data.
13. Sampling error reduced as the study remains with the same sample over time.
14. Enables clear recommendations for intervention to be made.
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1. Time-consuming – it takes a long time for the studies to be conducted and the results to emerge.
2. Problems of sample mortality heighten over time and diminish initial representativeness.
3. Control effects – repeated interviewing of the same sample influences their behaviour.
4. Intervening effects attenuate the initial research plan.
5. Problem of securing participation as it involves repeated contact.
6. Data, being rich at an individual level, are typically complex to analyze. |
Cross-sectional studies |
1. Snapshot of different samples at one or more points in time (synchronic analysis).
2. Large-scale and representative sampling.
3. Macro-level analysis.
4. Enables different groups to be compared.
5. Can be retrospective and/or prospective. |
1. Comparatively quick to conduct.
2. Comparatively cheap to administer.
3. Limited control effects as subjects only participate once.
4. Stronger likelihood of participation as it is for a single time.
5. Charts aggregated patterns.
6. Useful for charting population-wide features at one or more single points in time.
7. Enable researchers to identify the proportions of people in particular groups or states.
8. Large samples enable inferential statistics to be used, e.g. to compare subgroups within the sample.
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1. Do not permit analysis of causal relationships.
2. Unable to chart individual variations in development or changes, and their significance.
3. Sampling not entirely comparable at each round of data collection as different samples are used.
4. Can be time-consuming as background details of each sample have to be collected each time.
5. Omission of a single variable can undermine the results significantly.
6. Unable to chart changing social processes over time.
7. They only permit analysis of overall, net change at the macro-level through aggregated data. |
Trend Analysis |
1. Selected factors studied continuously over time.
2. Uses recorded data to predict future trends. |
1. Maintains clarity of focus throughout the duration of the study.
2. Enables prediction and projection on the basis of identified and monitored variables and assumptions. |
1. Neglects influence of unpredicted factors.
2. Past trends are not always a good predictor of future trends.
3. Formula-driven, i.e. could be too conservative or initial assumptions might be erroneous.
4. Neglects the implications of chaos and complexity theory, e.g. that long-range forecasting is dangerous.
5. The criteria for prediction may be imprecise. |
Retrospective longitudinal studies |
1. Retrospective analysis of history of a sample.
2. Individual- and micro-level data. |
1. Useful for establishing causal relationships.
2. Clear focus (e.g. how did this particular end state or set of circumstances come to be?).
3. Enables data to be assembled that are not susceptible to experimental analysis. |
1. Remembered information might be faulty, selective and inaccurate.
2. People might forget, suppress or fail to remember certain factors.
3. Individuals might interpret their own past behaviour in light of their subsequent events, i.e. the interpretations are not contemporaneous with the actual events.
4. The roots and causes of the end state may be multiple, diverse, complex, unidentified and unstraightforward to unravel.
5. Simple causality is unlikely.
6. A cause may be an effect and vice versa.
7. It is difficult to separate real from perceived or putative causes.
8. It is seldom easily falsifiable or confirmable. |
