Installation | Set up and plot example data | Add batch effects | Perform batch effect adjustment without confounders | Simple means | Means from marginal standardization | Inverse-probability weighting | Quantile regression | Quantile normalization | Perform batch effect adjustment in the presence of confounding | Set up example data with confounding present | For comparison: Batch effect adjustment ignoring confounding | Additional features | Missing values | Model diagnostics

Loading the package | Data handling | Generate a table design | Obtain Table 1 | Customize the table | Add more statistics per variable

Loading the package | Loading example data | Example 1: Basic use with binary outcomes | Example 2: Formatted output | Example 3: Swap rows and columns | Example 4: Survival outcomes, effect modifier, and confounder | Example 5: Two estimates using type and type2 | Example 6: Continuous outcomes, rounding, and trend (slope)

Example | Absolute estimates per exposure category | Comparative estimates with confidence intervals

Example | Absolute estimates per exposure category | Comparative estimates with confidence intervals | More on ratios of continuous outcomes

Basic example | Why do I get an error? | What is the design? | How do I handle missing data? | How do I add overall statistics? | How do I test for trend? | How do I show multiple exposures in the same table? | How do I change how results are rounded? | How can I create joint models? | How can I change the reference category? | How I do I change the level for confidence intervals? | How do I make rifttable calculate an estimand that is not built-in?

Example | Absolute estimates per exposure category | Comparative estimates with confidence intervals | Competing events | Weighted estimates | Clustering and robust variance

Installation | An example cohort study | Adjusted risk ratios | Adjusted risk differences | Accessing model coefficients | More post-estimation commands

Implemented model types | Model choice | Model comparisons

The basics | Choice of exposure variable | Bootstrap confidence intervals | Bootstrap repeats