Diagnosing Separation Phenomena in Latent Polyhedral Categorical Response Models

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Documentation for package ‘divoRce’ version 0.10-1

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acl_Xstar Function to calculate the negative structure vector matrix X* for an adjacent-category link model.
Alligators Untabeled alligator food choice data
bcl_Xstar Function to calculate the negative structure vector matrix X* for baseline-category outcomes.
b_Xstar Function to calculate the negative structure vector matrix X* for binary outcomes.
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_osm Separation check for ordered stereotype models.
checksep_sl Separation check for sequential (continuation-ratio) models.
cl_Xstar Function to calculate the negative 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
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.
HDSS Willingness to Share Health Data of Drexler (2025)
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_b 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_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_osm 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
osm_Xstar Function to calculate the negative structure vector matrix X* for an ordered stereotype model.
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_b Calculates recession cone for baseline-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.
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_osm 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.
Silvapulle Psychiatric Cases Classification based on GHQ of Silvapulle (1981)
struc_vec Function to calculate the structure vector matrix S for categorical outcomes.
titanic3 All people of age 3 in the Kaggle Titanic data set