CausalGPS 0.5.0 (2024-06-19)
CausalGPS 0.4.1 (2023-09-29)
CRAN release: 2023-09-29
CausalGPS 0.4.0 (2023-05-25)
CRAN release: 2023-05-25
Changed
- Docker image supports R 4.2.3
-
generate_syn_datasupportsvectorized_yto accelerate data generation. -
matching_fun–>dist_measure -
matching_l1–>matching_fn -
estimate_semipmetric_erfnow takes thegammodels optional arguments. -
estimate_pmetric_erfnow takes thegnmmodels optional arguments. -
trim_quantiles–>exposure_trim_qtls -
generate_pseudo_popfunction acceptsgps_objas an optional input. -
internal_useis not part of parameters forestimate_gpsfunction. -
estimate_gpsfunction only returnsid,w, and computedgpsas part of dataset. - Now the design and analysis phases are explicitly separated.
-
gps_model–>gps_density. Now it takes,normalandkerneloptions instead ofparametricandnon-parametricoptions.
CausalGPS 0.3.1 (2023-05-15)
CRAN release: 2023-05-16
Changed
- Some of unit tests have less accuracy to overcome the bug with
stats::densityfunction.
CausalGPS 0.3.0 (2023-02-15)
CRAN release: 2023-02-15
Changed
- Unit tests support new
wCorrrelease (#193). - Only optimized compilation is supported. In the previous versions, this approach is known as
optimzied_compile == TRUE.
CausalGPS 0.2.9 (2022-12-16)
CRAN release: 2022-12-16
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_erffunction, thematched_cwinput is now mandatory. - Internal kernel smoothing now uses
locpol::locpolfunction. - The entire data set is trimmed based on trimming quantiles.
-
earthandrangerare not installed automatically. They can be installed manually if needed. -
sysdata.rdais modified to reflect transition fromcounterandipwtocounter_weight -
counter_weightis used as a counter or weight, inmatchingorweightingapproaches.counterandipware dropped. -
sl_libbecomes a required argument. - The package has been transferred into NSAPH-Software Github account.
- Summary function of
gpsm_pspopS3 object returns details of the adjusting process.
Added
- Now
Kolmogorov-Smirnov(KS)statistics are provided for the computed pseudo population. -
effect sizefor the generated pseudo population is computed and reported. - Binary search approach is used when scale = 1.
-
pseodo_popalso includes covariate column names. -
compute_closest_wgps_helper_no_scis added to take care of the mostly used special case (scale = 1).
CausalGPS 0.2.8 (2022-06-22)
CRAN release: 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.
CausalGPS 0.2.6 (2021-09-06)
CRAN release: 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.
CausalGPS 0.2.4 (2021-07-11)
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