Surrogate 3.4

Surrogate 3.4.1

• Add the ICA.Sample.ControlTreat() function to quantify surrogacy in the single-trial causal-inference framework when data is only available for the control treatment.

Surrogate 3.4.0

• Added ICA_alpha_ContCont() to assess surrogacy using a Rényi divergence based family of metrics in the information-theoretic causal-inference framework.
• Added ICA_t() to assess surrogacy in the information-theoretic causal-inference framework assuming a multivariate t-distribution for the vector of potential outcomes.

Surrogate 3.3

Surrogate 3.3.0

• Added and updated functions for the survival-categorical, survival-binary, and survival-continuous settings in the meta-analytic framework.
• Added functions to perform the two-stage federated surrogacy evaluation.

Surrogate 3.3.1

• General implementation of the information-theoretic causal inference framework based on D-vine copula models for the ordinal-ordinal, ordinal-continuous, and continuous-continuous settings.

Surrogate 3.3.3

• Fix tests that fail on CRAN.

Surrogate 3.2

Surrogate 3.2.6

• Updated functions for the surrogate predictive function in the binary-continuous setting (information-theoretic causal inference framework).

Surrogate 3.2.5

• Added functions survbin() and survcat() to evaluate categorical surrogates for time-to-event true endpoints in the meta-analytic framework.

Surrogate 3.2.4

• In the sensitivity analyses, we now have to option to set conditional association parameters equal to each other through eq_cond_association
• Bug fixed in sensitivity_analysis_SurvSurv(). When the unidentifiable copula family was "clayton", then, if the copula parameter on Spearman’s rho scale was very close to zero, the conversion to the original copula parameter scale was wrong.

Surrogate 3.2.2

• Added uncertainty intervals to summarize sensitivity analyses
• Extended flexibility for survival-survival vine copula models and associated sensitivity analysis
• Add functions to evaluate multivariate surrogates in the meta-analytic framework

Surrogate 3.2.1

• Added ICA.BinCont.BS() function. This function allows for evaluating a continuous for a binary true endpoint in the information-theoretic causal inference framework. This function serves the same purpose as ICA.BinCont(), but additionally allows for taking sampling variability into account.

Surrogate 3.2.0

• Added a NEWS.md file to track changes to the package.