The key characteristics of a statistical study with generalizable results include:
1. Representative Sample
- The study must use a sample that accurately mirrors the relevant characteristics of the broader population. This means the sample should be sufficiently large and unbiased to reflect the population from which it is drawn
- Random sampling techniques are crucial to give every member of the population an equal chance of selection, enhancing representativeness
- Diverse sample selection covering different age groups, genders, ethnicities, and other demographics improves generalizability across subgroups
2. Well-Defined Target Population
- The population to which the results are intended to generalize must be clearly defined. Generalizability is about the relationship between the study sample and this target population
- The study sample should ideally be randomly drawn from this target population to ensure the sample average treatment effect approximates the population average treatment effect
3. Appropriate Research Design and Methods
- The study should be carefully designed to minimize bias and control confounding variables, ensuring internal validity, which supports external validity and generalizability
- Quantitative research methods, especially experimental designs with random assignment, provide a strong foundation for broad generalizability
- Using multiple methods or replicating the study in different settings can strengthen generalizability by testing consistency across contexts
4. Large and Varied Sample Size
- Larger sample sizes generally increase the ability to generalize results, although beyond a certain size (e.g., 10,000 subjects) increases may have diminishing returns
- Variation in the sample regarding demographics and other relevant factors helps ensure findings apply to a wider population
5. Consideration of Context and Environment
- Results should be applicable in different contexts and environments. Researchers need to document the study environment thoroughly so readers can judge transferability to other settings
- Generalizability involves assessing whether findings hold under different circumstances, measurements, and subject groups
6. Statistical and Theoretical Generalizability
- Statistical generalizability applies to quantitative studies and depends on representativeness and sample size
- Theoretical generalizability (or transferability) applies more to qualitative research but is related, as it involves applying findings to other contexts based on theory
In summary, a statistical study with generalizable results must have a representative and sufficiently large sample drawn from a clearly defined target population, use rigorous and unbiased research methods, and consider context and variability to ensure findings can be extended beyond the original study sample to the broader population or other settings
