Function reference • ecmeta.nsclc

Data preparation and exploration
`preprocess()`	Preprocess data
`new_analysis()`	New analysis object
`html_table(<analysis>)`	HTML analysis table
`count_missing()`	Count missing observations
`autoplot(<missing_counts>)`	Plot missing observations
`plot_density(<data.frame>)`	Density plot for continuous variable
`plot_bar()`	Bar plot for categorical variable
`count_by()`	Counts by group
Imputation
`impute_formula()` `add_impute_formula()`	Formulas for multiple imputation
`multi_impute()`	Multiple imputation
`observed_vs_imputed()`	Observed vs imputed data
`autoplot(<observed_vs_imputed>)`	Observed vs. imputed plot
Propensity scores Model, weight, and check balance
`get_ps_formula()` `add_ps_formula()`	Propensity score formulas
`make_xdata()`	Model data
`fit_ps()` `fit_ps_mi()`	Fit propensity score model
`predict_ps()`	Predict propensity scores
`psweight()`	Propensity score weighting
`plot_weights()`	Plot propensity score weights
`plot_ps()`	Plot propensity scores
`plot_density(<grouped_psweight_mi>)`	Density plots to check balance
`smd()`	Standardized mean differences
`smd_list()`	Standardized mean difference list
`autoplot(<smd>)` `autoplot(<smd_list>)`	Plot standardized mean differences
Average treatment effects Estimate average treatment effects with survival data
`surv_ate()` `map_surv_ate()`	Average treatment effects for survival data
`ps_surv()` `map_ps_surv()`	Propensity score survival analysis
`update(<surv_ate>)` `update(<grouped_surv_ate>)` `update(<grouped_ps_surv>)`	Update treatment effect estimates
`marginal_survival()`	Marginal survival curves
`autoplot(<grouped_marginal_survival>)`	Plot of marginal survival curve by group
`hazard_ratio()` `autoplot(<hazard_ratio>)`	Hazard ratios
`benchmark_hazard_ratios()` `autoplot(<benchmarked_hazard_ratios>)` `html_table(<benchmarked_hazard_ratios>)`	Benchmark hazard ratios
Meta-analytic cross validation
`ecmeta_lpo_cv()`	Meta-analytic leave-p-out cross validation
Utility functions
`label_ps_method()`	Labels for propensity score methods
`rbind_list()`	Row bind data frame like objects
`html_table()`	HTML table

Reference

Data preparation and exploration

Imputation

Propensity scores

Average treatment effects

Meta-analytic cross validation

Utility functions