ARMD                    Data of the Age-Related Macular Degeneration
                        Study
BifixedContCont         Fits a bivariate fixed-effects model to assess
                        surrogacy in the meta-analytic multiple-trial
                        setting (Continuous-continuous case)
BimixedContCont         Fits a bivariate mixed-effects model to assess
                        surrogacy in the meta-analytic multiple-trial
                        setting (Continuous-continuous case)
CIGTS                   Data of the Collaborative Initial Glaucoma
                        Treatment Study
CausalDiagramBinBin     Draws a causal diagram depicting the median
                        informational coefficients of correlation (or
                        odds ratios) between the counterfactuals for a
                        specified range of values of the ICA in the
                        binary-binary setting.
CausalDiagramContCont   Draws a causal diagram depicting the median
                        correlations between the counterfactuals for a
                        specified range of values of ICA or MICA in the
                        continuous-continuous setting
FixedContContIT         Fits (univariate) fixed-effect models to assess
                        surrogacy in the continuous-continuous case
                        based on the Information-Theoretic framework
ICA.BinBin              Assess surrogacy in the causal-inference
                        single-trial setting in the binary-binary case
ICA.BinBin.CounterAssum
                        ICA (binary-binary setting) that is obtaied
                        when the counterfactual correlations are
                        assumed to fall within some prespecified
                        ranges.
ICA.BinBin.Grid.Full    Assess surrogacy in the causal-inference
                        single-trial setting in the binary-binary case
                        when monotonicity for S and T is assumed using
                        the full grid-based approach
ICA.BinBin.Grid.Sample
                        Assess surrogacy in the causal-inference
                        single-trial setting in the binary-binary case
                        when monotonicity for S and T is assumed using
                        the grid-based sample approach
ICA.ContCont            Assess surrogacy in the causal-inference
                        single-trial setting (Individual Causal
                        Association, ICA) in the Continuous-continuous
                        case
ICA.Sample.ContCont     Assess surrogacy in the causal-inference
                        single-trial setting (Individual Causal
                        Association, ICA) in the Continuous-continuous
                        case using the grid-based sample approach
LongToWide              Reshapes a dataset from the 'long' format
                        (i.e., multiple lines per patient) into the
                        'wide' format (i.e., one line per patient)
MICA.ContCont           Assess surrogacy in the causal-inference
                        multiple-trial setting (Meta-analytic
                        Individual Causal Association; MICA) in the
                        continuous-continuous case
MICA.Sample.ContCont    Assess surrogacy in the causal-inference
                        multiple-trial setting (Meta-analytic
                        Individual Causal Association; MICA) in the
                        continuous-continuous case using the grid-based
                        sample approach
MarginalProbs           Computes marginal probabilities for a dataset
                        where the surrogate and true endpoints are
                        binary
MinSurrContCont         Examine the plausibility of finding a good
                        surrogate endpoint in the Continuous-continuous
                        case
MixedContContIT         Fits (univariate) mixed-effect models to assess
                        surrogacy in the continuous-continuous case
                        based on the Information-Theoretic framework
Pos.Def.Matrices        Generate 4 by 4 correlation matrices and flag
                        the positive definite ones
RandVec                 Generate random vectors with a fixed sum
Restrictions.BinBin     Examine restrictions in pi_{f} under different
                        montonicity assumptions for binary S and T
SPF.BinBin              Evaluate the surrogate predictive function
                        (SPF) in the binary-binary setting
Schizo                  Data of five clinical trials in schizophrenia
Schizo_Bin              Data of five clinical trials in Schizophrenia
                        (with binary outcomes).
Schizo_Bin_ST           Data of a clinical trial in Schizophrenia (with
                        binary outcomes, dataset 1).
Schizo_Bin_ST2          Data of a clinical trial in Schizophrenia (with
                        binary outcomes, dataset 2).
Schizo_PANSS            Longitudinal PANSS data of five clinical trials
                        in schizophrenia
Sim.Data.Counterfactuals
                        Simulate a dataset that contains
                        counterfactuals
Sim.Data.CounterfactualsBinBin
                        Simulate a dataset that contains
                        counterfactuals for binary endpoints
Sim.Data.MTS            Simulates a dataset that can be used to assess
                        surrogacy in the multiple-trial setting
Sim.Data.STS            Simulates a dataset that can be used to assess
                        surrogacy in the single-trial setting
Sim.Data.STSBinBin      Simulates a dataset that can be used to assess
                        surrogacy in the single trial setting when S
                        and T are binary endpoints
Single.Trial.RE.AA      Conducts a surrogacy analysis based on the
                        single-trial meta-analytic framework
UnifixedContCont        Fits univariate fixed-effect models to assess
                        surrogacy in the meta-analytic multiple-trial
                        setting (continuous-continuous case)
UnimixedContCont        Fits univariate mixed-effect models to assess
                        surrogacy in the meta-analytic multiple-trial
                        setting (continuous-continuous case)
plot Causal-Inference BinBin
                        Plots the (Meta-Analytic) Individual Causal
                        Association and related metrics when S and T
                        are binary outcomes
plot Causal-Inference ContCont
                        Plots the (Meta-Analytic) Individual Causal
                        Association when S and T are continuous
                        outcomes
plot Information-Theoretic
                        Provides plots of trial- and individual-level
                        surrogacy in the Information-Theoretic
                        framework
plot Meta-Analytic      Provides plots of trial- and individual-level
                        surrogacy in the meta-analytic framework
plot MinSurrContCont    Graphically illustrates the theoretical
                        plausibility of finding a good surrogate
                        endpoint in the continuous-continuous case
plot SPF BinBin         Plots the surrogate predictive function (SPF).
summ.ICA.By.Mon         Provide summary measures for ICA in the bin-bin
                        setting for each of the monotonicity scenarios
