facebookresearch/balance 0.6.0

0.6.0 (2023-04-05)

on GitHub

New Features

• Variance of the weighted mean
  • Add the var_of_weighted_mean function (from balance.stats_and_plots.weighted_stats import var_of_weighted_mean):
    Computes the variance of the weighted average (pi estimator for ratio-mean) of a list of values and their corresponding weights.
    • Added the var_of_mean option to stat in the descriptive_stats function (based on var_of_weighted_mean)
    • Added the .var_of_mean() method to BalanceDF.
  • Add the ci_of_weighted_mean function (from balance.stats_and_plots.weighted_stats import ci_of_weighted_mean):
    Computes the confidence intervals of the weighted mean using the (just added) variance of the weighted mean.
    • Added the ci_of_mean option to stat in the descriptive_stats function (based on ci_of_weighted_mean). Also added kwargs support.
    • Added the .ci_of_mean() method to BalanceDF.
    • Added the .mean_with_ci() method to BalanceDF.
    • Updated .summary() methods to include the output of ci_of_mean.
• All bar plots now have an added ylim argument to control the limits of the y axis.
  For example use: plot_dist(dfs1, names=["self", "unadjusted", "target"], ylim = (0,1))
  Or this: s3_null.covars().plot(ylim = (0,1))
• Improve 'choose_variables' function to control the order of the returned variables
  • The return type is now a list (and not a Tuple)
  • The order of the returned list is based on the variables argument. If it is not supplied, it is based on the order of the column names in the DataFrames. The df_for_var_order arg controls which df to use.
• Misc
  • The _prepare_input_model_matrix and downstream functions (e.g.: model_matrix, sample.outcomes().mean(), etc) can now handle DataFrame with special characters in the column names, by replacing special characters with '_' (or '_i', if we end up with columns with duplicate names). It also handles cases in which the column names have duplicates (using the new _make_df_column_names_unique function).
  • Improve choose_variables to control the order of the returned variables
    • The return type is now a list (and not a Tuple)
    • The order of the returned list is based on the variables argument. If it is not supplied, it is based on column names in the DataFrames. The df_for_var_order arg controls which df to use.

Contributors

@talgalili, @SarigT