multibias 1.7.2

Added multibias_plot() to visualize sensitivity analysis results
When using validation data in multibias_adjust() the function now incorporates uncertainty of the effect estimates from the validation data by sampling from each estimate’s mean and SE. Now, when using validation data, the confidence intervals from multibias bootstrapped results will represent two sources of uncertainty: random error and systematic error.
Added FAQ documentation

multibias 1.7.1

Updated code with dynamic formula construction so that there is no limit to the number of known confounders one can include when using bias_params as an input for multibias_adjust()
multibias_adjust() now has built in bootstrapping
Added summary() method to data_observed

Created bias_params class to handle bias parameter inputs to multibias_adjust()
Replaced the various adjust() functions with a single multibias_adjust() function. Users now specify the biases they want to adjust for in the data_observed object. Bias adjustment formulas are now found in the bias_params documentation.
The user now specifies biases for adjustment in the bias input of data_observed
Removed evans data; now only used in vignette

The following functions now accept data_validation as an input for bias adjustment:
- adjust_em_om.R
- adjust_em_sel.R
Bug fixes for validation data input in adjust_em.R and adjust_om.R
Bug fixes for data and printing in data_observed and data_validation

Created new class data_observed to represent observed causal data
All adjust functions now take data_observed as input
Created new class data_validation to represent causal data that can be used as validaiton data for bias adjustment
The following functions now accept data_validation as an input for bias adjustment:
- adjust_uc.R
- adjust_em.R
- adjust_om.R
- adjust_sel.R

All exposure misclassificaiton naming changed from emc changed to em
All outcome misclassificaiton naming changed from omc changed to om
Added lifecycle badges for above function renames
Merged adjust_multinom_uc_em_sel into adjust_uc_em_sel
Merged adjust_multinom_uc_om_sel into adjust_uc_om_sel
The following functions now support more flexible combinations of continuous and binary exposure-outcome variables:
- adjust_uc_em_sel.R
- adjust_uc_om_sel.R

Merged adjust_multinom_emc_omc into adjust_emc_omc
Merged adjust_multinom_uc_emc into adjust_uc_emc
Merged adjust_multinom_uc_omc into adjust_uc_omc
The following functions now support more flexible combinations of continuous and binary exposure-outcome variables:
- adjust_emc_sel (exposure must be binary)
- adjust_omc_sel (outcome must be binary)
- adjust_uc_emc (exposure must be binary)
- adjust_uc_omc (outcome must be binary)
- adjust_multinom_uc_emc (exposure must be binary)
- adjust_multinom_uc_omc (outcome must be binary)
Expanded the number of known confounders in dataframes:
- df_omc_sel
- df_omc_sel_source

The following functions now support more flexible combinations of continuous and binary exposure-outcome variables:
- adjust_uc
- adjust_emc (exposure must be binary)
- adjust_omc (outcome must be binary)
- adjust_sel
- adjust_uc_sel
Expanded the number of known confounders in dataframes:
- df_uc_omc
- df_uc_omc_source
- df_uc_emc
- df_uc_emc_source
Dataframes df_uc and df_uc_source now both have continuous and binary exposures and outcomes.

Added two functions for simultaneous adjustment of uncontrolled confounding, outcome misclassification, and selection bias: adjust_uc_omc_sel & adjust_multinom_uc_omc_sel.
Added dataframes with uncontrolled confounding, outcome misclassification, and selection bias: df_uc_omc_sel and df_uc_omc_sel_source.
Expanded the number of known confounders in dataframes:
- df_uc_sel
- df_uc_sel_source

Added two functions for simultaneous adjustment of exposure misclassification and outcome misclassification: adjust_emc_omc & adjust_multinom_emc_omc.
Added dataframes with exposure misclassification and outcome misclassification: df_emc_omc and df_emc_omc_source.
Expanded the number of known confounders in dataframes:
- df_emc_sel
- df_emc_sel_source

Added a function for simultaneous adjustment of outcome misclassification and selection bias: adjust_omc_sel.
Added dataframes with outcome misclassification and selection bias: df_omc_sel and df_omc_sel_source.
Expanded the number of known confounders in dataframes:
- df_uc
- df_uc_source
- df_emc
- df_emc_source
- df_omc
- df_omc_source
- df_sel
- df_sel_source

Added two functions for simultaneous adjustment of uncontrolled confounding and outcome misclassification: adjust_uc_omc and adjust_multinom_uc_omc.
Added dataframes with uncontrolled confounding and outcome misclassification: df_uc_omc and df_uc_omc_source.

adjust_sel had been weighing with the probability of selection instead of the inverse probability of selection.