Package: ham 1.2.0.9000

Healthcare Analysis Methods (ham) | 1. Introduction | 2. Descriptive and inferential statistics | Group level 95% confidence intervals over 12 months (t distribution) | Rolling 6-month averages by quartiles of age (Q1 - Q4) | Graph the results | Between-group variance and within-group clustering | Graph the confidence interval trend results | 3. Linear and logistic regression | OLS or linear regression | ham provides coefficient interpretations with interpret() | Logistic regression | Logistic regression interpretations | Poisson regression | Poisson regression interpretations | OLS top-coding and propensity scores | model results | Inverse Probability of Treatment Weighting using the propensity score (IPW) | Weighted least squares model results | importance | Graph importance | Graph a summary of the coefficients | 4. Differences-in-Differences | DID model for length of stay using assess() | Code to view DID model results | Code to get the coefficient interpretations | View a partial prediction plot | View DID 30-day readmissions results | 5. Interrupted Time Series | ITS model 1 | View ITS model 1 results | interpret coefficients | Graph ITS model 1 | ITS model 2 | View ITS model 2 results | interpret ITS 2 coefficients | Graph ITS model 2 | ITS model 3 | Plot the summary coefficients | View ITS model 3 results | ITS model 4: 30-day death (mortality) | View ITS model 4 results | interpret ITS 4 coefficients | Graph ITS model 4 | ITS model 5 | Graph ITS model 5 results | An example of calculating Cronbach's alpha: | Interpret Cronbach's alpha: | 7. Discussion | 8. References

1. Introduction | Bayes() | plot.Bayes() | 2. Diagnostics: 'dxa', 'dxd', 'dxg', 'dxt' | interpretations | 3. Posterior summary: 'post' | 4a. Posterior Predictive Check: 'check' | 4b. Checking the regression trend line: 'check' | 5. Hierarchical or Multilevel Model summary: 'multi' | 6. Target setting: 'target' | 7. Gelamn's R^2: 'r2'

1. Introduction | 2. $\bar{X}$ charts | 3. p-chart | 4. u-chart

1. Introduction | 1. Model classification | 2. Decision Curve Analysis: Net Benefit | 3. Decision Curve Analysis (DCA): Interventions Saved