Sampling and generalisability in developmental research: Comparison of random and convenience samples of older adults
Bibliographic record
Abstract
Research in the developmental sciences is based largely on samples of convenience rather than samples drawn at random from the population. The important question of whether results observed in samples of convenience generalise to the larger population has not been studied directly. Because of demographic growth in the proportion of older adults in the population and increases in diversity across the lifespan, it is especially important to address this issue in aging adults. We compared the performance of older adults (65–100 years) on demographic and psychological measures for a random sample of community dwelling adults and two samples of convenience. Significant differences were observed on less than half the variables. When differences were present, participants in the convenience samples were advantaged compared to participants from the random sample. Differences were larger in some domains than others but remained small to moderate in magnitude. There were minimal differences in between-person variability and patterns of correlations among variables between the convenience and random samples. Results indicate the need for additional studies contrasting random and convenience samples to explore the parameters of external validity in psychological aging research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.345 | 0.510 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".