bartMachine - Bayesian Additive Regression Trees

An advanced implementation of Bayesian Additive Regression Trees with expanded features for data analysis and visualization.

Last updated 1 years ago

openjdk

6.08 score 6 packages 296 scripts 2.2k downloads

GreedyExperimentalDesign - Greedy Experimental Design Construction

Computes experimental designs for a two-arm experiment with covariates via a number of methods: (0) complete randomization and randomization with forced-balance, (1) Greedily optimizing a balance objective function via pairwise switching. This optimization provides lower variance for the treatment effect estimator (and higher power) while preserving a design that is close to complete randomization. We return all iterations of the designs for use in a permutation test, (2) The second is via numerical optimization (via 'gurobi' which must be installed, see <https://www.gurobi.com/documentation/9.1/quickstart_windows/r_ins_the_r_package.html>) a la Bertsimas and Kallus, (3) rerandomization, (4) Karp's method for one covariate, (5) exhaustive enumeration to find the optimal solution (only for small sample sizes), (6) Binary pair matching using the 'nbpMatching' library, (7) Binary pair matching plus design number (1) to further optimize balance, (8) Binary pair matching plus design number (3) to further optimize balance, (9) Hadamard designs, (10) Simultaneous Multiple Kernels. In (1-9) we allow for three objective functions: Mahalanobis distance, Sum of absolute differences standardized and Kernel distances via the 'kernlab' library. This package is the result of a stream of research that can be found in Krieger, A, Azriel, D and Kapelner, A "Nearly Random Designs with Greatly Improved Balance" (2016) <arXiv:1612.02315>, Krieger, A, Azriel, D and Kapelner, A "Better Experimental Design by Hybridizing Binary Matching with Imbalance Optimization" (2021) <arXiv:2012.03330>.

Last updated 1 years ago

3.86 score 1 packages 16 scripts 300 downloads

SeqExpMatch - Sequential Experimental Design via Matching on-the-Fly

Generates the following sequential two-arm experimental designs: (1) completely randomized (Bernoulli) (2) balanced completely randomized (3) Efron's (1971) Biased Coin (4) Atkinson's (1982) Covariate-Adjusted Biased Coin (5) Kapelner and Krieger's (2014) Covariate-Adjusted Matching on the Fly (6) Kapelner and Krieger's (2021) CARA Matching on the Fly with Differential Covariate Weights (Naive) (7) Kapelner and Krieger's (2021) CARA Matching on the Fly with Differential Covariate Weights (Stepwise) and also provides the following types of inference: (1) estimation (with both Z-style estimators and OLS estimators), (2) frequentist testing (via asymptotic distribution results and via employing the nonparametric randomization test) and (3) frequentist confidence intervals (only under the superpopulation sampling assumption currently). Details can be found in our publication: Kapelner and Krieger "A Matching Procedure for Sequential Experiments that Iteratively Learns which Covariates Improve Power" (2020) <arXiv:2010.05980>. We now offer support for incidence, count, proportion and survival (with censoring) outcome types. We also have support for adding responses whenever they become available, and we can impute missing data in the subjects' covariate records (where each covariate record can thereby have different information). On the inference side, there is built-in support for many types of parametric models such as random effects for incidence outcomes and count outcomes. There is Kaplan-Meier estimation, weibull and coxph models for survival outcomes.

Last updated 3 months ago

3.48 score 1 scripts 157 downloads

fastLogisticRegressionWrap - Fast Logistic Regression Wrapper

Provides very fast logistic regression with coefficient inferences plus other useful methods such as a forward stepwise model generator (see the benchmarks by visiting the github page at the URL below). The inputs are flexible enough to accomodate GPU computations. The coefficient estimation employs the fastLR() method in the 'RcppNumerical' package by Yixuan Qiu et al. This package allows their work to be more useful to a wider community that consumes inference.

Last updated 1 years ago

2.70 score 1 stars 2 scripts 203 downloads

OptimalRerandExpDesigns - Optimal Rerandomization Experimental Designs

This is a tool to find the optimal rerandomization threshold in non-sequential experiments. We offer three procedures.

Last updated 4 years ago

2.70 score 1 scripts 125 downloads

bartMachineJARs - bartMachine JARs

These are bartMachine's Java dependency libraries. Note: this package has no functionality of its own and should not be installed as a standalone package without bartMachine.

Last updated 2 years ago

openjdk

2.69 score 7 packages 9 scripts 2.3k downloads

PTE - Personalized Treatment Evaluator

We provide inference for personalized medicine models. Namely, we answer the questions: (1) how much better does a purported personalized recommendation engine for treatments do over a business-as-usual approach and (2) is that difference statistically significant?

Last updated 6 years ago

2.39 score 27 scripts 142 downloads

ICEbox - Individual Conditional Expectation Plot Toolbox

Implements Individual Conditional Expectation (ICE) plots, a tool for visualizing the model estimated by any supervised learning algorithm. ICE plots refine Friedman's partial dependence plot by graphing the functional relationship between the predicted response and a covariate of interest for individual observations. Specifically, ICE plots highlight the variation in the fitted values across the range of a covariate of interest, suggesting where and to what extent they may exist.

Last updated 2 years ago

1.59 score 37 scripts 1.1k downloads

optDesignSlopeInt - Optimal Designs for Estimating the Slope Divided by the Intercept

Aids practitioners to optimally design experiments that measure the slope divided by the intercept and provides confidence intervals for the ratio.

Last updated 1 years ago

1.00 score 2 scripts 144 downloads

GreedyExperimentalDesignJARs - GreedyExperimentalDesign JARs

These are GreedyExperimentalDesign Java dependency libraries. Note: this package has no functionality of its own and should not be installed as a standalone package without GreedyExperimentalDesign.

Last updated 6 years ago

openjdk

1.00 score 149 downloads