Alligators              Untabeled alligator food choice data
HDSS                    Willingness to Share Health Data of Drexler
                        (2025)
Silvapulle              Psychiatric Cases Classification based on GHQ
                        of Silvapulle (1981)
acl_Xstar               Function to calculate the structure vector
                        matrix X* for an adjacent-category link model.
bcl_Xstar               Function to calculate the structure vector
                        matrix X* for baseline-category outcomes.
check_ovl               General overlap check.
check_sep               General separation check. This calls to the
                        appropriate low-level function.
check_sep_acl           Separation check for adjacent-category link
                        models.
check_sep_b             Separation check for binary models.
check_sep_bcl           Separation check for baseline category models.
check_sep_cl            Separation check for cumulative link models.
check_sep_osm           Separation check for ordered stereotype models.
check_sep_sl            Separation check for sequential
                        (continuation-ratio) models.
cl_Xstar                Function to calculate the structure vector
                        matrix X* for a cumulative link model.
create_bseq             Creates a list of data for a sequence of binary
                        models from a sequential (continuation ratio)
                        model. It splits the data according to the
                        forward sequential mechanism.
csepdat1                Toy data set with complete separation
csepdat2                Toy data set with complete separation
csepdatm                Toy data set with complete separation
csepdato                Toy data set with complete separation
detect_sepcols          This function identifies the columns in a
                        design matrix that are responsible for
                        separation. It calls lower level functions if
                        given an argument or chooses based on the
                        response type.
detect_sepcols_acl      This function identifies the columns in a
                        design matrix for an adjacent-category link
                        model that have an infinite MLE, due to
                        separation. Note this is due to separation
                        which includes the case of a design matrix that
                        doesn't have full rank.
detect_sepcols_b        This function identifies the columns in a
                        binary model design matrix that are responsible
                        for separation.
detect_sepcols_bcl      This function identifies the columns in a
                        design matrix for a baseline-category link
                        model that have an infinite MLE, due to
                        separation. Note this is due to separation
                        which includes the case of a design matrix that
                        doesn't have full rank.
detect_sepcols_cl       This function identifies the columns in a
                        design matrix for a cumulative link model that
                        have an infinite MLE, due to separation. Note
                        this is due to separation which includes the
                        case of a design matrix that doesn't have full
                        rank.
detect_sepcols_osm      This function identifies the columns in a
                        design matrix for an ordered stereotype model
                        that have an infinite MLE, due to separation.
                        Note this is due to separation which includes
                        the case of a design matrix that doesn't have
                        full rank.
detect_sepcols_sl       This function identifies the columns in a
                        sequential model design matrix that are
                        responsible for separation.
diagsep                 Detailed separation diagnostic for all
                        categorical outcomes.
diagsep_acl             Detailed separation diagnostic for
                        adjacent-category link ordinal response models.
diagsep_b               Detailed separation diagnostic for binary
                        outcomes.
diagsep_bcl             Detailed separation diagnostic for
                        baseline-category link models.
diagsep_cl              Detailed separation diagnostic for cumulative
                        link ordinal response models.
diagsep_osm             Detailed separation diagnostic for ordered
                        stereotype models.
diagsep_sl              Detailed separation diagnostic for sequential
                        (continuation-ratio) ordinal response models.
iris2                   Adapted Iris Dataset
linearities             This function calculates the linearities in the
                        data, so the row vectors for which there is no
                        separation.  If this is an empty set or of
                        length 0, then we have overlap.
linearities_acl         This function calculates the linearities in the
                        data for an adjacent-category link model, so
                        the row vectors for which there is no
                        separation. If this is an empty set or of
                        length 0, then we have overlap.
linearities_bcl         This function calculates the linearities in the
                        data for a baseline-category link model, so the
                        row vectors for which there is no separation.
                        If this is an empty set or of length 0, then we
                        have overlap.
linearities_cl          This function calculates the linearities in the
                        data for a cumulative link model, so the row
                        vectors for which there is no separation. If
                        this is an empty set or of length 0, then we
                        have overlap.
linearities_osm         This function calculates the linearities in the
                        data for an ordered stereotype model, so the
                        row vectors for which there is no separation.
                        If this is an empty set or of length 0, then we
                        have overlap.
linearities_sl          This function calculates the linearities in the
                        data for an sequential link model, so the row
                        vectors for which there is no separation. If
                        this is an empty set or of length 0, then we
                        have overlap.
make_yx                 This function is meant to set up a response
                        variable and a design matrix from a
                        formula-data combination for the pre-fit
                        separation check functions.
nsduh2019               A snapshot of the NSDUH 2019 data
ohiovoters              Voters in Ohio
osm_Xstar               Function to calculate the structure vector
                        matrix X* for an ordered stereotype model.
overlap_fc              A fraction check for overlap.
overlap_qc              A quick check for overlap.
ovldat1                 Toy data set with overlap.
ovldat2                 Toy data set with overlap.
ovldatm                 Toy data set with overlap.
ovldato                 Toy data set with overlap.
print.sepmod            Print generic for sepmod classes
print.sepmod_sl         Print generic for sepmod_sl classes
qcsepdat1               Toy data set with quasi-complete separation
qcsepdat2               Toy data set with quasi-complete separation
qcsepdatm               Toy data set with quasi-complete separation
qcsepdato               Toy data set with quasi-complete separation
reccone                 Calculates recession cone for categorical data
                        models.
reccone_acl             Calculates recession cone for adjacent-category
                        link models.
reccone_bcl             Calculates recession cone for baseline-category
                        link models.
reccone_cl              Calculates recession cone for cumulative link
                        models.
reccone_osm             Calculates recession cone for ordered
                        stereotype models.
reccone_sl              Calculates recession cone for sequential link
                        models.
separation_qc           A quick check for separation.
sepobs_acl              Identify the observations that cause separation
                        in adjacent-category link ordinal response
                        models.
sepobs_b                Observations that cause separation in binary
                        outcomes.
sepobs_bcl              Identify the observations that cause separation
                        in baseline-category link categorical response
                        models.
sepobs_cl               Identify the observations that cause separation
                        in cumulative link ordinal response models.
sepobs_osm              Identify the observations that cause separation
                        in ordered stereotype models.
sepobs_sl               Detect observations with separation for
                        sequential (continuation-ratio) ordinal
                        response models.
struc_vec               Function to calculate the structure vector
                        matrix X* for categorical outcomes.
summary.sepmodb         Summary generic for sepmodb classes
titanic3                All people of age 3 in the Kaggle Titanic data
                        set
