Additional file 1 of Evaluation of negative binomial and zero-inflated negative binomial models for the analysis of zero-inflated count data: application to the telemedicine for children with medical complexity trial
Creators: name: Lee, Kyung Hyun
name: Pedroza, Claudia
name: Avritscher, Elenir B. C.
name: Mosquera, Ricardo A.
name: Tyson, Jon E.
Publisher: name: figshare
Year: 2023
Subjects: subject: Medicine
subject: Biotechnology
subject: Sociology
subject: FOS: Sociology
subject: Biological Sciences not elsewhere classified
subject: Mathematical Sciences not elsewhere classified

description: Additional file 1: Fig. S1. Detailed flow chart of the observed data analysis (DD: Data-derived). Fig. S2. Detailed flow chart of the data simulation (construction of synthetic data). Fig. S3. Detailed flow chart of the analysis of simulated data and logistic regression. Table S1. Median and interquartile range (IQR) of a treatment group coefficient from the fitted model under two different true models using the observed outcomes (top: number of serious illness episodes; middle: days in hospital; bottom: care days outside the home). Table S2. Bias, mean squared error (MSE), and coverage for a treatment group coefficient for the secondary outcomes (top: days in hospital; bottom: care days outside the home). Table S3. Percentage of the sim. models that prefer an NB model over a ZINB model. Table S4. Details of differences of AIC between sim. NB and ZINB models. Table S5. Unique characteristics (median with IQR) of the synthetic secondary outcomes (Var.=variance, % of 0’s = percentage of zero counts). Table S6. Sensitivity analysis with different sample sizes (60, 80, 100, 200, 600, 800). The outcome being used is the number of serious illness episodes (primary). Abs. bias: Absolute bias. Table S7. Sensitivity analysis with different sample sizes (60, 80, 100, 200, 600, 800). The outcome being used are secondary outcomes (care days outside the home, days in hospital). Abs. bias: Absolute bias. Fig. S4. A violin plot of lower (left) and upper (right) bounds of the confidence intervals (CIs) obtained from the sim. NB models under a true ZINB distribution. A blue vertical dotted line represents a DD coefficient (β_DD; -0.64). Mean and standard deviation are represented by the red circle and red solid line in each violin plot. Fig. S5. Correlation plot using 8 unique characteristics of data using synthetic primary outcomes (serious illness episodes). Eight unique characteristics of the outcomes include overall mean, overall variance, percentage of zero counts, mean/variance/skewness of the non-zero part, and MLEs of p and r. Fig. S6. Adjusted (A) and unadjusted (B) odds ratio for a preference for a ZINB model (over an NB model in terms of AIC) with the primary outcome (serious illness episodes) regardless of the type of DD models. Fig. S7. From the DD NB model: Adjusted (left) and unadjusted (right) odds ratio for a preference for a ZINB model (over an NB model in terms of AIC) with the primary outcome (serious illness episodes). Fig. S8. From the DD ZINB model: Adjusted (left) and unadjusted (right) odds ratio for a preference for a ZINB model (over an NB model in terms of AIC) with the primary outcome (serious illness episodes). Fig. S9. Adjusted (A) and unadjusted (B) odds ratio for a preference for a ZINB model (over an NB model in terms of AIC) with the secondary outcome (care days outside the home) regardless of the type of DD models. Fig. S10. From the DD NB model: Adjusted (left) and unadjusted (right) odds ratio for a preference for a ZINB model (over an NB model in terms of AIC) with the secondary outcome (care days outside the home. Fig. S11. From the DD ZINB model: Adjusted (left) and unadjusted (right) odds ratio for a preference for a ZINB model (over an NB model in terms of AIC) with the secondary outcome (care days outside the home). Fig. S12. Adjusted (A) and unadjusted (B) odds ratio for a preference for a ZINB model (over an NB model in terms of AIC) with the secondary outcome (days in hospital) regardless of the type of DD models. Fig. S13. From the DD NB model: Adjusted (left) and unadjusted (right) odds ratio for a preference for a ZINB model (over an NB model in terms of AIC) with the secondary outcome (days in hospital). Fig. 14. From the DD NB model: Adjusted (left) and unadjusted (right) odds ratio for a preference for a ZINB model (over an NB model in terms of AIC) with the secondary outcome (days in hospital). Table S8. Unadjusted odds ratios with 95% confidence intervals (CIs) based on the unstandardized (raw) predictors regardless of the type of DD models. Asterisk indicates p-value &lt; 0.05.