CausalGPS 0.5.1 (2025-01-10)

Removed

• Strict tests.

CausalGPS 0.5.0 (2024-06-19)

Added

• estimate_gps now accepts formula for generating GPS object.
• estimate_gps now has functions for generic plot, print, and summary functions.
• trim_it function.

Removed

• preprocess_data function.
• trim_gps function.

CausalGPS 0.4.2 (2024-04-13)

Added

• heads-up message about changes in the software design that will be implemented in CausalGPS version 0.5.x.

CausalGPS 0.4.1 (2023-09-29)

Added

• Extra step to check consistency of delta_n with exposure range.
• Software paper examples were added.

Changed

• Plotting pseudo population includes object details. Set include_details = TRUE.
  *generate_pseudo_pop does not take Y as an input.

CausalGPS 0.4.0 (2023-05-25)

Changed

• Docker image supports R 4.2.3
• generate_syn_data supports vectorized_y to accelerate data generation.
• matching_fun –> dist_measure
• matching_l1 –> matching_fn
• estimate_semipmetric_erf now takes the gam models optional arguments.
• estimate_pmetric_erf now takes the gnm models optional arguments.
• trim_quantiles –> exposure_trim_qtls
• generate_pseudo_pop function accepts gps_obj as an optional input.
• internal_use is not part of parameters for estimate_gps function.
• estimate_gps function only returns id, w, and computed gps as part of dataset.
• Now the design and analysis phases are explicitly separated.
• gps_model –> gps_density. Now it takes, normal and kernel options instead of parametric and non-parametric options.

Added

• estimate_npmetric_erf supports both locpol and KernSmooth approaches.
• There is gps_trim_qtls input parameter to trim data samples based on gps values.
• Now users can also collect the original data in the pseudo population object.

Fixed

• A bug with swapping transformed covairates with original one.

CausalGPS 0.3.1 (2023-05-15)

Changed

• Some of unit tests have less accuracy to overcome the bug with stats::density function.

CausalGPS 0.3.0 (2023-02-15)

Changed

• Unit tests support new wCorr release (#193).
• Only optimized compilation is supported. In the previous versions, this approach is known as optimzied_compile == TRUE.

Added

• The earth package is part of suggested packages.

CausalGPS 0.2.9 (2022-12-16)

Fixed

• fixed a bug based on covariate balance threshold (#178, @naeemkh).
• estimate_npmetric_erf assigns user-defined log file.

Changed

• The process now prints the progress message based on the selected thresholds.
• In estimate_npmetric_erf:
  • matched_Y –> m_Y
  • matched_w –> m_w
  • matched_cw –> counter_weight
• In estimate_npmetric_erf function, the matched_cw input is now mandatory.
• Internal kernel smoothing now uses locpol::locpol function.
• The entire data set is trimmed based on trimming quantiles.
• earth and ranger are not installed automatically. They can be installed manually if needed.
• sysdata.rda is modified to reflect transition from counter and ipw to counter_weight
• counter_weight is used as a counter or weight, in matching or weighting approaches. counter and ipw are dropped.
• sl_lib becomes a required argument.
• The package has been transferred into NSAPH-Software Github account.
• Summary function of gpsm_pspop S3 object returns details of the adjusting process.

Added

• Now Kolmogorov-Smirnov(KS) statistics are provided for the computed pseudo population.
• effect size for the generated pseudo population is computed and reported.
• Binary search approach is used when scale = 1.
• pseodo_pop also includes covariate column names.
• compute_closest_wgps_helper_no_sc is added to take care of the mostly used special case (scale = 1).

Removed

• Dropped importing KernSmooth and tidyr packages.
• pred_model argument dropped. The package only predicts using SuperLearner.

CausalGPS 0.2.8 (2022-06-22)

Fixed

• Message for not implemented methods changed to reduce misunderstanding.
• Empty counter will raise error in estimating non-parametric response function.

Changed

• matching_l1 returns frequency table instead of entire vector.
• Vectorized population compilation and used data.table for multi-thread assignment.
• Removed nested parallelism in compiling pseudo population, which results in close control on memory.
• estimate_npmetric_erf also returns optimal h and risk values.

Added

• estimate_gps returns the optimal hyperparameters.
• estimate_gps returns S3 object.
• Internal xgboost approach support verbose parameter.
• Pseudo-population object now report the parameters that are used for the best covariate balance.

CausalGPS 0.2.7 (2022-02-04)

Fixed

• Naming covariate balance scores.

Changed

• Restarting adaptive approach to keep trying up to maximum attempt.

Added

• Synthetic data (synthetic_us_2010)
• Check on not defined covariate balance (absolute_corr_fun, absolute_weighted_corr_fun)
• Covariate balance threshold type: mean, median, maximal.
• Improved test coverage.
• Singularity definition file.

CausalGPS 0.2.6 (2021-09-06)

Added

• added the status of optimized compile to generate_pseudo_pop function output.
• compute_closest_wgps accepts the number of user-defined threads.

Changed

• Vignette file names.
• The trim condition from > and < into >= and <=.
• Removed seed input from generate_syn_data function. In R package, setting seed value inside function is not recommended. Users can set the seed before using the function.
• OpenMP uses user defined number of cores.

Fixed

• Initial covariate balance for weighted approach. The counter column was not preallocated correctly.
• Counter value for compiling. The initial value was set to one, which, however, zero is the correct one.
• Private variable issue with OpenMP.
• Fixed OpenMP option on macOS checks.

Removed

CausalGPS 0.2.5 (2021-07-23)

Changed

• User needs to activate the logger

Fixed

• CRAN package URLs are in canonical forms.

CausalGPS 0.2.4 (2021-07-11)

Added

• OpenMP for Rcpp code
• optimized_compile
• log_system_info()
• Frequently asked questions
• logo

Changed

• estimate_gps.Rmd
• estimate_semi_erf -> estimate_semipmetric_erf
• estimate_erf -> estimate_npmetric_erf
• estimate_hr -> estimate_pmetric_erf
• gen_pseudo_pop -> generate_pseudo_pop
• gen_syn_data -> generate_syn_data
• estimate_erf accepts counter as an input
• estimate_erf can use multiple cores
• generating_pseudo_population.Rmd
• estimate_erf function description
• estimate_hr function description
• estimate_semi_erf function description
• compute_risk function description and return value
• outcome_models.Rmd
• generate_synthetic_data.Rmd

Fixed

• Rcpp parLapply worker processors arguments

Removed

• running_appr

CausalGPS 0.2.3 (2021-05-12)

Fixed

• Fixed documentations

CausalGPS 0.2.2 (2021-05-12)

Added

• estimate_semi_erf
• estimate_hr

Changed

• Package name: GPSmatching –> CausalGPS

GPSmatching 0.2.1 (2021-04-23)

Added

• User defined bin sequence in compiling pseudo population.
• Non-parametric option for estimating GPS.
• Adaptive approach to transform features in training sessions.
• Cpp code for computing pair of w and GPS.
• set_logger function.
• Customized wrapper for ranger package.
• Extended plot function for gen_pseudo_pop object (plot.R).
• Extended plot function for estimate_erf object (plot.R).
• Extended print function for estimate_erf object (print.R).
• test-estimate_erf.R.
• create_weighting.R.
• Steps for adding test data into ‘sysdata.rda’.
• weighting option as causal inference approach.
  
• absolute_weighted_corr_fun.R
• Testing and running example guidelines for developers
• Customized wrapper for xgboost package.
• param as an argument to accept hyperparameters from users.

Changed

• R dependency 2.7 –> 3.5
• mclapply –> parLapply
• estimate_erf output returns S3 object.
• test-Covariate_balance.R –> test-absolute_corr_fun.R
• covariate_balance.R –> absolute_corr_fun.R
• User needs to pass m_xgboost instead of SL.xgboost to use XGBoost package for prediction purposes.

Fixed

• mclapply memory issue (compute_closest_wgps.R).

GPSmatching 0.2.0 (2021-03-01)

Added

• Covariate balance check for categorical data.
• Contribution guidelines
• Parallel flag in training models (mcSuperLearner)
• gen_syn_data function for generating synthetic data
• Unittest for gen_syn_data
• Function to compute residuals and unittest
• Function to impute NA values based on density and unittest
• Function to separate prediction model training (train_it)
• Function to separate min and max value estimation and unittest
• Function to find the closest data based on GPS and w
• Wrapper function to generate pseudo population and test it for covariate balance (gen_pseudo_pop)
• Function to estimate only GPS value (estimate_gps)
• Helper function to take the input data + GPS values and return pseudo population based on selected causal inference approach. The output of this function may or may not satisfy the covariate balance test. (compile_pseudo_pop)
• check_args function to check availability of the required parameters.
• check_covar_balance function to check if the generated pseudo population statistically acceptable.
• create_matching function to generate pseudo population based on matching approach.
• acknowledgments to index file

Changed

• create_matching only generates matched dataset.
• Covariate_balance.R –> covariate_balance.R
• matching_smooth –> estimate_erf.R
• risk_fun –> compute_risk
• smooth_fun –> smooth_erf
• hatvals –> estimate_hat_vals
• kernel_fun –> generate_kernel
• GPSmatching-package.R –> gpsmatching_package.R
• GPSmatching_smooth.R –> gpsmatching_smooth.R

Removed

• GPSmatching.R functions are separated into smaller functions, and the file is removed.