| acl_Xstar |
Function to calculate the structure vector matrix X* for an adjacent-category link model. |
| Alligators |
Untabeled alligator food choice data |
| 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. |
| detect_sepobs_acl |
Identify the observations that cause separation in adjacent-category link ordinal response models. |
| detect_sepobs_b |
Observations that cause separation in binary outcomes. |
| detect_sepobs_bcl |
Identify the observations that cause separation in baseline-category link categorical response models. |
| detect_sepobs_cl |
Identify the observations that cause separation in cumulative link ordinal response models. |
| detect_sepobs_osm |
Identify the observations that cause separation in ordered stereotype models. |
| detect_sepobs_sl |
Detect observations with separation for sequential (continuation-ratio) ordinal response models. |
| 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. |
| HDSS |
Willingness to Share Health Data of Drexler (2025) |
| 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_b |
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_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_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. |
| separation_qc |
A quick check for separation. |
| 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. |
| 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. |
| sepcols_b |
This function identifies the columns in a binary model design matrix that are responsible for separation. |
| 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. |
| 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. |
| 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. |
| sepcols_sl |
This function identifies the columns in a sequential model design matrix that are responsible 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. |
| Silvapulle |
Psychiatric Cases Classification based on GHQ of Silvapulle (1981) |
| 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 |
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