Changelog
Source:NEWS.md
[2024-11-26] margot 0.3.0.3
Fixed
margot_amelia_to_mice()
- fixed to be unconstrained to previous workflow.
[2024-11-11] margot 0.3.0.2
Fixed
margot_plot()
label now reads “causal difference” rather than “causal risk difference”.
[2024-11-09] margot 0.3.0.1
[2024-11-06] margot 0.3.0.0
New
-
margot_make_table()
- flexible longitudinal tables -
margot_amelia_to_mice()
- convertsAmelia
output tomice
output.
[2024-10-30] margot 0.2.3.80
New
-
margot_count_ids()
- track cumulative counts of participants, returning participants,
Improved
-
margot_count_dyads()
- more informative information.
[2024-10-26] margot 0.2.3.13
[2024-10-26] margot 0.2.3.12
Improved
-
margot_wide_machine()
correctly handles NA values at baseline, and prints out message
[2024-10-23] margot 0.2.3.11
Improved
-
margot_save_png()
better defaults -
margot_plot()
enhancements, and improved documentation
[2024-10-23] margot 0.2.3.10
Improved
-
margot_save_png()
flexibly handles any plot object, not merely ggplot2 objects.
[2024-10-22] margot 0.2.3.9
Improved
-
margot_interpret_marginal()
gives correct interpretation of ‘strong’ evidence using Evalues.
[2024-10-02] margot 0.2.3.8
-
margot_process_longitudinal_data_wider()
performance enhancement. Users can save the outcome variable even if previous exposures are missing. Useful forlmtp
survival models
[2024-09-27] margot 0.2.3.7 :)!
Improved
-
margot_process_longitudinal_data_wider()
performance enhancement -
margot_wide_machine()
simplified. We now have a time-varying treatment workflow in place!
[2024-09-27] margot 0.2.3.6
New
margot_wide_machine()
converts wide data to long data so using indicators for missing observations, which allows for non-parametric stacked learning inlmtp
without multiple-imputation assumptions. Also handles more than three time-points. Optionalimputation_method = 'mice
allows users to impute, while also creating NA dummy variables for non-parametric learning.margot_process_longitudinal_data_wider()
extends flexibility ofmargot_process_longitudinal_data()
to more than three waves, and allows users to specify variable names.
[2024-09-26] margot 0.2.3.5
New
- helper function
back_transform_estimates()
is unique for the marginal plots and marginal interpretation, to avoid confusions with back-transforming helpers for split-points in policy trees.
Improved
-
margot_plot()
, andmargot_interpret_marginal()
produce interpretable results. Fixed issue withmargot_plot()
when risk ratios are selected, where colours were not being plotted.
[2024-09-25] margot 0.2.3.4
New
-
margot_plot_slope_covariate_combo()
- batch multiplemargot_plot_slope_covariate()
plots onto one graph usingpatchwork
.
Improved
-
margot_plot_slope_covariate()
improved for flexibility
[2024-09-25] margot 0.2.3.3
Improved
-
margot_plot_histogram()
now take optionalvertical_facets
parameter, allowing for more interpretable time-series graphs. - placed all internal function under
helpers.R
in the R directory, to avoid clutter.
[2024-09-25] margot 0.2.3.2
Improved
-
margot_plot()
margot_interpret_marginal()
now back transform values to data scale.
[2024-09-24] margot 0.2.3.1
Improved
-
margot_plot_policy_tree()
,margot_plot_decision_tree()
,margot_interpret_policy_tree()
,margot_plot_qini_tree()
use same global function names. New helper functions back-transform logged values (as well as z-transformed values) so that we get interpretations on the data scale for variables that have been log-transformed. This aids with interpretation.
[2024-09-20] margot 0.2.3.0
New
- Refactored causal tree graphs and interpretations for flexible labelling and for providing both standardised results (where relevant), and results on the data scale. Makes the interpretation of policies easier to understand.
-
margot_count_dyads()
counts dyads in a longitudinal dataset. -
margot_summary_panel()
summaries participants by panel wave; counts unique participants by wave, … -
margot_interpret_policy_batch()
interprets the policytree results.
Improved
-
margot_summary_tables()
- now pass multiple tables, better exposure plots. -
margot_interpret_policy_tree()
- refactored: now returns results on data scale, better labels. -
margot_plot_policy_tree()
- refactored: now returns results on data scale, better labels.
[2024-09-19] margot 0.2.1.64
Improved
-
margot_plot()
,margot_interpret_marginal()
,group_tab()
overhauled so that now we get reporting back-tranformed from standardised effects to effects on the data scale – greatly benefiting interpretations. -
transform_to_original_scale()
new helper introduced to back-transform estimates.
[2024-09-18] margot 0.2.1.63
-
margot_save_png()
replacesmargot_plot_save_png()
for consistent function labelling, and to spare a burden of remembering function names.
[2024-09-17] margot 0.2.1.62
-
margot_compare_groups()
added bold formatting to alert readers to reliable group differences
Improved
-
margot_interpret_qini()
- now formats tables to alert readers to where prioritising results are reliably worse or better than than none.
[2024-09-17] margot 0.2.1.60
Improved
-
margot_plot_create_options()
updated to work with improve plotting workflow
Deprecated
-
compute_difference()
now use the more generalmargot_compare_groups()
workflow.
Removed
- Removed the following deprecated functions from vignettes, instead use https://github.com/go-bayes/boilerplate
boilerplate_measures
boilerplate_methods_additional_sections
boilerplate_methods
boilerplate_methods_causal_interventions
boilerplate_methods_confounding_control
boilerplate_methods_eligibility_criteria
boilerplate_methods_identification_assumptions
boilerplate_methods_missing_data
boilerplate_methods_sample
boilerplate_methods_statistical_estimator
boilerplate_methods_target_population
boilerplate_methods_variables
create_ordered_variable_custom
margot_compute_gender_weights
margot_create_bibliography
margot_create_database
margot_grf_subset_table
margot_merge_databases
manager_boilerplate_measures
compute_difference()
[2024-09-17] margot 0.2.1.59
New
-
margot_plot_save_png()
saves a margot_plot output graph as a png, user can change width, heigh, dpi, and specify a path…
Improved
-
margot_plot()
automatic saving of the output with optional timestamps -
margot_plot_multi_arm()
modified to work with new and improvedmargot_plot()
[2024-09-16] margot 0.2.1.58
New
-
margot_compare_groups()
compare treatment effects by groups and evaluate evidence for differences
[2024-09-16] margot 0.2.1.57
New
-
margot_plot_multi_arm()
wrapper formargot_plot
that enables each plots/tables for multi arm treatment models
Improved
- reporting of multi arm treatment models in
margot_plot_qini()
is easier to follow. -
margot_lmtp()
now has automatic saving of models with optional prefix label and optional time-stamping. Also actually saves table when computing contrasts with only the null model.
[2024-09-16] margot 0.2.1.56
Improved
-
margot_interpet_qini()
robust for both binary and multi-arm treatments. -
margot_plot_qini()
correct label for binarhy treatments -
margot_batch_policy_tree()
correctly modified function added: commputes multiple ‘spends’
[2024-09-15] margot 0.2.1.55
Improved
-
extract_qini_data()
improved handling ofmargot_multi_arm_causal_forest()
- numerous plot functions enhanced to produce “NZ” instead of “Nz”
[2024-09-12] margot 0.2.1.54
New
-
margot_summary_cate_difference_gain()
computes the difference in average gains and the integrated difference between a reference curve (maq object) and a comparison curve at a specified spend level – to see if there is support for CATEs
Improved
-
compute_qini_curves_multi_arm()
- modified so that we can now get quantitative estimates for support for CATEs -
margot_multi_arm_causal_forest()
- enhanced in several ways, for example to supportmargot_summary_cate_differences()
-
margot_causal_forest()
- likewise enhanced. -
margot_batch_policy()
now outputs `margot_summary_cate_difference_gain() models by default
[2024-09-12] margot 0.2.1.53
Improved
-
margot_summary_tables()
plots take upper case letters, remove ’_’ -
margot_adjust_weights()
censored individuals are assigned zero weights, and only uncensored individuals contribute to the final analysis.
[2024-09-12] margot 0.2.1.52
Improved
- Fixed
margot_plot_response_timeline()
to print dates, and to optionally save a ’png` image.
[2024-09-12] margot 0.2.1.51
Improved
-
margot_plot_discontinuity()
andmargot_plot_slope()
have correct end years (+1 final wave, as waves overlap years)
[2024-09-12] margot 0.2.1.50
New
-
margot_plot_boxplot_covariate()
descriptive trends by groups
Improved
-
margot_plot_slope_covariate()
automatic title, save png, and optional time stamp -
margot_plot_individual_responses()
fixed so there is no missingness
[2024-09-12] margot 0.2.1.49
Improved
- reverted
compute_qini_curves
(only works with binary vars) -
margot_causal_forest()
now working again
[2024-09-12] margot 0.2.1.48
Improved
margot_multi_arm_causal_forest()
-
extract_qini_data()
improved to work withmargot_multi_arm_causal_forest()
New
-
compute_qini_curves_multi_arm()
internal function to supportmargot_multi_arm_causal_forest()
[2024-09-11] margot 0.2.1.47
Improved
- Coordinated the following functions to play well with
margot_multi_arm_causal_forest()
margot_plot_qini()
- `extract_qini_data()``
compute_qini_curves()
[2024-09-11] margot 0.2.1.45
[2024-09-02] margot 0.2.1.44
Improved
-
margot_plot_individual_responses()
now plotting all cases by default. Defaultrandom_draws
of 100.
[2024-09-02] margot 0.2.1.43
Improved
-
margot_plot_histogram()
, optional coloured mean/sd lines.
[2024-09-02] margot 0.2.1.42
Improved
-
margot_plot_individual_responses()
. Now handles factors, and robust to missing waves. -
margot_plot_boxplot()
different colours for boxplots if a single variable is passed over multiple waves.
[2024-09-02] margot 0.2.1.41
New features
-
margot_plot_individual_responses()
. New function to allow random plotting of responses in a subset of the sample, useful for investigating individual trajectories of change. -
margot_plot_boxplot()
Now user supplieswave
values, allowing more flexible and precise plotting of intervals. Has optional prefixes. The coordinates of the graph may be optionally flipped.
[2024-09-02] margot 0.2.1.40
New features
-
margot_plot_categorical()
for visualising categorical data distributions. -
margot_plot_shift()
for visualising shifts in data distributions with highlighted ranges.
Deprecations
The following functions have been deprecated in favor of the new functions:
-
margot_plot_hist()
is deprecated. Usemargot_plot_histogram()
instead. -
coloured_histogram()
is deprecated. Usemargot_plot_histogram()
instead. -
coloured_histogram_shift()
is deprecated. Usemargot_plot_shift()
instead.coloured_histogram_quantiles()
is deprecated. Usemargot_plot_categorical()
instead.
These deprecated functions will continue to work but will issue warnings. They will be removed in a future version of the package.
[2024-09-02] margot 0.2.1.39
Improved
-
margot_plot_slope()
allows faceting
[2024-09-02] margot 0.2.1.38
New
-
margot_plot_histogram()
new histogram that’s more informative and more robust than previous attempts. Can be used for multiple variables and multiple waves.
Improved
-
margot_plot_boxplot()
made robust to single outcome in single wave.
[2024-09-02] margot 0.2.1.37
-
margot_plot_discontinuity()
,margot_plot_slope()
,margot_plot_slope_covariate()
automatically print number of unique participants and unique number of observations in the title, if no title is passed.
[2024-09-02] margot 0.2.1.36
Improved
-
margot_plot_discontinuity()
now being read to namespace.
[2024-09-01] margot 0.2.1.35
New
-
margot_plot_slope()
descriptive trends in continuous variables over time; user may pass historical events which are denoted by dashed vertical lines on the plot. -
margot_plot_slope_covariate()
descriptive trends by covariates over time. -
margot_plot_bloxplot()
descriptive trends using boxplots + facets. -
prepare_panel_data()
helper function to get panel data into shape for plotting response timelines for repeated measures studies. -
margot_response_timeline()
plot histogram of response timelines for repeated measures studies.
Improved
-
here_save_qs()
andhere_read_qs()
report where and object was saved and how large it is. -
here_save()
andhere_read()
, ditto, and also ask users to specify a directory path, defaulting topush_mods
if none is supplied
[2024-09-01] margot 0.2.1.34
New
-
margot_plot_discontinuity()
create longitudinal graphs
Improved
-
margot_size()
has cli alerts
[2024-08-30] margot 0.2.1.33
New
-
read_multiple_images()
utility function to read batchs of images, for presentations, articles etc.
[2024-08-29] margot 0.2.1.31
Improved
-
margot_batch_policy()
allows user to save plots automatically, with different sizes and resolutions.
[2024-08-29] margot 0.2.1.30
Improved
-
margot_subset_model()
returns subset of results the user requests.
[2024-08-29] margot 0.2.1.29
New
-
margot_subset_model()
subsets causal forests for both categorial and binary exposures.
Deprecated
-
margot_grf_subset_table()
, functions replaced bymargot_subset_model()
, use this new function instead.
[2024-08-28] margot 0.2.1.28
New
-
margot_plot_exposure()
- utility to plot change in the exposure variable from baseline. -
margot_size()
- utility to check size of object
[2024-08-27] margot 0.2.1.26
Improved
-
margot_plot()
- consistent names for results table if these are modified using the newlabel_mapping
option. -
here_save_qs()
andhere_read_qs()
minor tweaks.
[2024-08-27] margot 0.2.1.25
-
margot_plot()
andmargot_plot_create_options()
now allow custom labels, which flexibly combine with defaults.
[2024-08-27] margot 0.2.1.24
Improved
- robust reporting/error handling in
margot_causal_forest()
, and its helper funcitoncompute_qini_curves()
[2024-08-26] margot 0.2.1.23
Deprecations
boilerplate_measures()
is deprecated. Useboilerplate::boilerplate_report_variables()
instead.boilerplate_methods_causal_interventions()
is deprecated. Useboilerplate::boilerplate_report_causal_interventions()
instead.boilerplate_methods_confounding_control()
is deprecated. Useboilerplate::boilerplate_report_confounding_control()
instead.boilerplate_methods()
is deprecated. Useboilerplate::boilerplate_report_methods()
instead.boilerplate_methods_eligibility_criteria()
is deprecated. Useboilerplate::boilerplate_report_eligibility_criteria()
instead.boilerplate_methods_identification_assumptions()
is deprecated. Useboilerplate::boilerplate_report_identification_assumptions()
instead.boilerplate_methods_missing_data()
is deprecated. Useboilerplate::boilerplate_report_missing_data()
instead.boilerplate_methods_sample()
is deprecated. Useboilerplate::boilerplate_report_sample()
instead.boilerplate_methods_statistical_estimator()
is deprecated. Useboilerplate::boilerplate_report_statistical_estimator()
instead.boilerplate_methods_target_population()
is deprecated. Useboilerplate::boilerplate_report_target_population()
instead.boilerplate_methods_variables()
is deprecated. Useboilerplate::boilerplate_report_variables()
instead.margot_create_database()
is deprecated. Useboilerplate::boilerplate_manage_measures()
instead.manager_boilerplate_measures()
is deprecated. Useboilerplate::boilerplate_manage_measures()
instead.margot_create_bibliography()
is deprecated. Useboilerplate::boilerplate_report_measures()
instead.margot_merge_databases()
is deprecated. Useboilerplate::boilerplate_merge_databases()
instead. (Note the plural ‘databases’ in the new function name.)to obtain these new functions, use
devtools::install_github("go-bayes/boilerplate")
[2024-08-21] margot 0.2.1.15
Improved
-
margot_plot_policy_tree()
,margot_plot_qini
,margot_plot_decision_tree
defaults to nice labels, with informative messages.
[2024-08-21] margot 0.2.1.14
New
-
margot_interpret_marginal
has consistent syntax withmargot_plot
. -
transform_table_rownames
to allow for nicer tables with clear labels. - overhauled
margot_plot
function so that it produces nice labels, and so that it also generates an interpretation.
[2024-08-19] margot 0.2.1.11
[2024-08-19] margot 0.2.1.10
Improved
-
boilerplate_measures
overhauled to allow bibliography by sections (for outcomewide studies) - considerably improved reporting in
boilerplate_methods
, including: selective sections to report. - overhauled
boilerplate_methods
for simple and clear reporting - simplified
biolerplate_methods_variables
to act mostly as a wrapper forboilerplate_measures
[2024-08-18] margot 0.2.1.8
New
-
boilerplate_methods
function allows first pass automated reporting. - helper functions include:
boilerplate_methods_sample
,boilerplate_methods_eligibility_criteria
,boilerplate_methods_identification_assumptions
,boilerplate_methods_statistical_estimator
,boilerplate_methods_confounding_control
,boilerplate_methods_missing_data
,boilerplate_methods_causal_interventions
- implemented
[2024-08-17] margot 0.2.1.7
[2024-08-16] margot 0.2.1.6
[2024-08-14] margot 0.2.1.3
New
-
margot_propensity_model_and_plots
a one stop shop for evaluating balance on the treatment: plots & diagnostics generated.
Restored
-
coloured_histogram()
back by popular demand.
[2024-08-11] margot 0.2.1.0
New
-
margot_plot_policy_combo
: creates a combination plot formargot_plot_decision_tree
andmargot_plot_policy_tree()
, easing the burden of interpretation.
Improved
-
margot_plot_decision_tree
: policy action leafs different colours (user may specify palette). Defaults toggokabeito::scale_fill_okabe_ito()
to matchmargot_plot_policy_tree()
-
margot_policy_tree
outputs amargot_plot_policy_combo
in addition to the other otuputs.
[2024-08-11] margot 0.2.0.9
Fixed
-
margot_plot_policy_tree
correctly renders decision tree, allows for individual plots for decision leafs, and collects guides. - error in rendering of
margot_plot_decision_tree
, fixed: function now includes internal tests. - removed
split_vars
from themargot_causal_forest
andmargot_mulit_arm_causal_forest
[2024-08-10] margot 0.2.0.8
[2024-08-9] margot 0.2.0.7
New
-
margot_interpret_policy_tree
interprets policy_tree outputs with outputs in either markdown or formats. -
margot_policy_tree
wrapsmargot_interpret_policy_tree
,margot_plot_policy_tree
,margot_qini_plot
and a decision tree visualisation within one function.
Improved
-
margot_plot
will now work even if no title or subtitle is passed. -
margot_plot_policy_tree
: focus is not simply on plotting, rather than doing both plotting and interpreting. -
margot_interpret_table
: no longer requires specification of estimate. General explanation printed separately (as it is only used once).
[2024-08-8] margot 0.2.0.6
[2024-08-7] margot 0.2.0.4
New
-
margot_process_longitudinal_data
orders correctly forlmtp
models by updating the censoring columnnot_lost
such that it handles missing responses as well as attrition. The function additionally automatically dummy codes ordinal variables and standardises continuous variables. Presently it is only implemented for three waves, but in the future it will be expanded to handle arbitrarily many.
[2024-08-7] margot 0.2.0.3
[2024-08-7] margot 0.2.0.2
Deprecations
-
coloured_histogram()
andcoloured_histogram_quantile()
are deprecated. Now use the newmargot_plot_hist()
instead. -
create_ordered_variable_custom
is deprecated. Now usecreated_ordered_variable
function withcustom_breaks = c(..)
to obtain custom breaks.
New
-
margot_plot_hist()
for plotting distributions of the exposure variable
margot 0.2.0
- improved subgroup comparison function
- deprecated
compare_group_means
function, withcompare_group
allowing for contrasts of on both the causal difference and relative risk scales. - new wrapper functions functions for
grf
plus visualising results.
margot 0.1.2.1
- group_tab now works under the hood of margot_plot, so no need to specify explicitly
- group_tab now allows custom order for plot, not just by decreasing effect size
- numerous small enhancements to older parametric model options
- new logo