A comparison of change point models with application to longitudinal lung function measurements in children with cystic fibrosis
Bibliographic record
Abstract
Cystic fibrosis (CF) is a hereditary lung disease characterized by loss of lung function over time. Lung function in CF is believed to decline at a higher rate during the adolescence period. It has been also hypothesized that there is a subgroup of individuals for whom lung disease remains relatively stable with only a slight decline over their lifetime. Using data from the University of Colorado CF Children's Registry, we investigate four change point models to model the decline of lung function in children and adolescents: (i) a two-component mixture random change point model, (ii) a two-component mixture-fixed change point model, (iii) a random change point model, and (iv) a fixed change point model. The models are investigated through posterior predictive simulation at the individual and population levels, and a simulation study examining the effects of model misspecification. The data support the mixed random change point model as the preferred model, with roughly 30% of adolescents experiencing a steady decline of 0.5 %FEV1 per year and 70% experiencing an increase in decline of 4.4 %FEV1 per year beginning on average at 14.6 years of age. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.083 | 0.172 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".