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

multibias 1.7

• 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

multibias 1.6.3

• Created a pkgdown web page: www.paulbrendel.com/multibias
• Refined the vignette, including a new NHANES analysis

multibias 1.6.2

• The following functions now accept data_validation as an input for bias adjustment:
  • adjust_om_sel.R
  • adjust_uc_sel.R
  • adjust_uc_em.R
  • adjust_uc_om.R
  • adjust_uc_em_sel.R
  • adjust_uc_om_sel.R

multibias 1.6.1

• 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

multibias 1.6

• 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

multibias 1.5.3

• 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

multibias 1.5.2

• 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

multibias 1.5.1

• 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.

multibias 1.5.0

New features

• 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

multibias 1.4.0

New features

• 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

Bug fixes

• Improved some of the documentation of equations.

multibias 1.3.0

New features

• 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

Bug fixes

• Fixed bug in adjust_omc that appears when using three confounders

multibias 1.2.1

• Moved examples from README to vignette.

multibias 1.2.0

New features

• 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.

Bug fixes

• None

multibias 1.1.0

New features

• Created new function to adjust for outcome misclassification: adjust_omc.
• Added dataframes for all single bias scenarios:
  • df_emc
  • df_emc_source
  • df_omc
  • df_omc_source
  • df_sel
  • df_sel_source
  • df_uc
  • df_uc_source

Bug fixes

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

multibias 1.0.0

• Initial CRAN submission.