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CausalQueries
View on CRAN: Click
here
Download and install CausalQueries package within the R console
Install from CRAN:
install.packages("CausalQueries")
Install from Github:
library("remotes")
install_github("cran/CausalQueries") Install by package version:
library("remotes")
install_version("CausalQueries", "1.4.4") Attach the package and use:
library("CausalQueries")
Maintained by
Till Tietz
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-06-03
Latest Update: 2025-07-22
Description:
Users can declare binary causal models, update beliefs about causal types given data and calculate arbitrary estimands. Model definition makes use of 'dagitty' functionality. Updating is implemented in 'stan'. The approach used in 'CausalQueries' is a generalization of the 'biqq' models described in "Mixing Methods: A Bayesian Approach" (Humphreys and Jacobs, 2015, ). The conceptual extension makes use of work on probabilistic causal models described in Pearl's Causality (Pearl, 2009, ).
How to cite:
Till Tietz (2020). CausalQueries: Make, Update, and Query Binary Causal Models. R package version 1.4.4, https://cran.r-project.org/web/packages/CausalQueries. Accessed 05 Jun. 2026.
Previous versions and publish date:
0.0.3 (2020-06-03 18:20), 0.1.0 (2022-06-28 00:20), 0.1.1 (2023-08-29 13:20), 1.0.0 (2023-10-13 20:30), 1.0.1 (2023-10-19 23:30), 1.0.2 (2024-01-15 22:10), 1.1.0 (2024-04-10 15:50), 1.1.1 (2024-04-26 11:00), 1.2.1 (2024-11-06 01:00), 1.3.0 (2024-12-14 07:50), 1.3.1 (2024-12-17 16:10), 1.3.2 (2025-01-22 15:00), 1.3.3 (2025-02-22 12:20), 1.4.3 (2025-07-22 23:41), 1.4.4 (2025-12-21 05:10)
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Other R packages that CausalQueries depends,
imports, suggests or enhances
Complete documentation for CausalQueries
Functions, R codes and Examples using
the CausalQueries R package
Some associated functions: CausalQueries-package . CausalQueries_internal_inherit_params . add_dots . add_wildcard . all_data_types . causal_type_names . check_string_input . clean_condition . clean_param_vector . clean_params . collapse_data . collapse_nodal_types . complements . data_to_data . data_type_names . decreasing . default_stan_control . democracy_data . draw_causal_type . drop_empty_families . expand_data . expand_nodal_expression . expand_wildcard . get_ambiguities_matrix . get_causal_types . get_data_families . get_event_prob . get_nodal_types . get_param_dist . get_parameter_matrix . get_parameter_names . get_parents . get_parmap . get_prior_distribution . get_query_types . get_type_names . get_type_prob . get_type_prob_multiple . gsub_many . includes_var . increasing . interacts . interpret_type . is_a_model . is_improper . list_non_parents . make_ambiguities_matrix . make_data . make_data_single . make_events . make_model . make_nodal_types . make_par_values . make_parameter_matrix . make_parmap . make_prior_distribution . minimal_data . minimal_event_data . n_check . nodes_in_statement . non_decreasing . non_increasing . observe_data . parameter_setting . perm . plot_dag . prep_stan_data . prior_setting . query_distribution . query_model . query_to_expression . realise_outcomes . restrict_by_labels . restrict_by_query . reveal_outcomes . set_ambiguities_matrix . set_confound . set_parameter_matrix . set_parmap . set_prior_distribution . set_restrictions . set_sampling_args . simulate_data . st_within . strategy_statements . substitutes . te . type_matrix . unpack_wildcard . update_causal_types . update_model . var_in_query .
Some associated R codes: CausalQueries-package.R . clean_params.R . data.R . data_helpers.R . draw_causal_type.R . get_ambiguities_matrix.R . get_causal_types.R . get_event_prob.R . get_nodal_types.R . get_parents.R . get_query_types.R . get_type_helpers.R . get_type_prob.R . helpers.R . internal_inherit_params.R . make_data.R . make_models.R . make_par_values.R . map_query_to_causal_type.R . map_query_to_nodal_type.R . misc.R . parmap.R . plot_dag.R . prep_stan_data.R . query_helpers.R . query_model.R . realise_outcomes.R . set_confounds.R . set_parameter_matrix.R . set_parameters.R . set_prior_distribution.R . set_priors.R . set_restrictions.R . simulate_events.R . stanmodels.R . update_model.R . zzz.R . Full CausalQueries package functions and examples
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