Additional file 1 of Comparison of statistical and machine learning models for healthcare cost data: a simulation study motivated by Oncology Care Model (OCM) data
Additional file 1: Figure S1A-D: RMSEs estimated from the five models with varied sample sizes. S1A: Gamma distribution, S1B: Weibull distribution, S1C: Heteroscedastic log-normal distribution, S1D: Heavy-tailed distribution. Results were plotted based on 1000 bootstrapped samples except for correctly specified and main effects-only Gamma GLM for heavy-tailed distribution (N = 200). Results using Gamma GLM with correct specification of interaction and non-linear terms for 200 samples, plotted based on the 286 converged models. Results using Gamma GLM with main effects only for the same scenario were plotted based on the 680 converged models.
Resource information
- Authors
- Mazumdar, Madhu, Lin, Jung-Yi Joyce, Zhang, Wei, Li, Lihua, Liu, Mark, Dharmarajan, Kavita, Sanderson, Mark, Isola, Luis, Hu, Liangyuan
- Research area
- Artificial intelligence
- Research topics
- Medicine, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, Mathematical Sciences not elsewhere classified
- Publication date
- 2020
- DOI
- 10.6084/m9.figshare.12197202
- Upstream last modified
- Mar 9, 2026
- License
- Creative Commons Attribution 4.0 International
- Last record update
- Nov 6, 2026
About this resource
Additional file 1: Figure S1A-D: RMSEs estimated from the five models with varied sample sizes. S1A: Gamma distribution, S1B: Weibull distribution, S1C: Heteroscedastic log-normal distribution, S1D: Heavy-tailed distribution. Results were plotted based on 1000 bootstrapped samples except for correctly specified and main effects-only Gamma GLM for heavy-tailed distribution (N = 200). Results using Gamma GLM with correct specification of interaction and non-linear terms for 200 samples, plotted based on the 286 converged models. Results using Gamma GLM with main effects only for the same scenario were plotted based on the 680 converged models. Results using Gamma GLM, PLAQR estimating 50th percentile on original scale, and RF with original scale of cost are shown.