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)
check_overlap           General overlap check.
checksep_acl            Separation check for adjacent-category link
                        models.
checksep_b              Separation check for binary models.
checksep_bcl            Separation check for baseline category models.
checksep_cl             Separation check for cumulative link models.
checksep_os             Separation check for ordered stereotype models.
checksep_sl             Separation check for sequential
                        (continuation-ratio) models.
checksep_worker         General separation check worker function.
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
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_os              Detailed separation diagnostic for ordered
                        stereotype models.
diagsep_sl              Detailed separation diagnostic for sequential
                        (continuation-ratio) ordinal response models.
diagsep_worker          Detailed separation diagnostic for all
                        categorical outcomes.
iris2                   Adapted Iris Dataset
linearities             This function calculates the linearities in the
                        negative structure vector matrix X*, 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
                        negative structure vector matrix X* 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
                        negative structure vector matrix X* 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
                        negative structure vector matrix X* 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_os          This function calculates the linearities in the
                        negative structure vector matrix X* 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
                        negative structure vector matrix X* 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
overlap_quick_check     A quick check for overlap.
overlap_sequential_check
                        A sequential 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_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_os              Calculates recession cone for ordered
                        stereotype models.
reccone_sl              Calculates recession cone for sequential link
                        models.
recession_cone          Calculates recession cone for categorical data
                        models.
separation_columns      Identify separation columns
separation_quick_check
                        A quick check for separation.
separation_rows         Identify the rows in the design/structure
                        vector matrix that cause separation.  It calls
                        lower level functions if given an argument or
                        chooses based on the response type.
sepcols_acl             Identify separation columns in
                        adjacent-category models
sepcols_b               Identify separation columns for binary models
sepcols_bcl             Identify separation columns in
                        baseline-category models
sepcols_cl              Identify separation columns in cumulative link
                        models
sepcols_os              Identify separation columns in ordered
                        stereotype models
sepcols_sl              Identify separation columns in sequential
                        models
seprows_acl             Identify the rows in data matrix that cause
                        separation in adjacent-category link ordinal
                        response models.
seprows_b               Identify rows in the data matrix that cause
                        separation for binary models.
seprows_bcl             Identify the rows in the data matrix that cause
                        separation in baseline-category link
                        categorical response models.
seprows_cl              Identify the rows in the data matrix that cause
                        separation in cumulative link ordinal response
                        models.
seprows_os              Identify the rows in the data matrix that cause
                        separation in ordered stereotype models.
seprows_sl              Detect design matrix rows with separation for
                        sequential (continuation-ratio) ordinal
                        response models.
structure_vectors       Structure Vector S3 Generic
titanic3                All people of age 3 in the Kaggle Titanic data
                        set
