Reporting Sample Size Calculation in Randomized Clinical Trials Published in 4 Orthodontic Journals
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to describe sample size calculations in randomized clinical trials (RCTs) published in four orthodontic journals. METHODS: This cross-sectional study evaluated 142 RCTs published from 2015 to 2019 in the four journals with the highest impact factor in orthodontics according to SCIMAGO 2018 ranking. Two trained and experienced orthodontists assessed if the RCTs evaluated reported their sample size calculations, and if they adequately described the criteria for the calculations, including the level of significance, test power, precision or effect size (clinically relevant difference), and expected variability. The reporting of sample size calculation was considered adequate when the above four criteria were described. RESULTS: We identified 120 publications (84.5%) reporting the sample size calculation, but only 70 (58.3%) fully described the above parameters. Inadequate calculation included failure to report the confidence level (ranging from 0% to 12.9%), test power (ranging from 0% to 20%), effect size (ranging from 0% to 22.5%) and expected variability (ranging from 22.6% to 80%). According to the journal, some parameters of sample size calculation were more frequently reported. CONCLUSION: RCTs published in four leading orthodontic journals frequently do not report the parameters used for sample size calculations.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Reporting · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | MetaresearchBibliometrics Domain: Reporting · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.940 | 0.994 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.019 | 0.007 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.069 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".