Package index • dsOMOPClient

All functions

as.data.frame(<dsomop_result>): Convert dsomop_result to data.frame
`$`(<dsomop_result>): Access dsomop_result elements with backward compatibility
ds.omop.achilles.analyses(): List available Achilles analyses
ds.omop.achilles.catalog(): Get Achilles analysis catalog
ds.omop.achilles.distribution(): Get Achilles distribution results
ds.omop.achilles.heel(): Get Achilles Heel data-quality warnings (per site)
ds.omop.achilles.results(): Get Achilles count results
ds.omop.achilles.status(): Check Achilles availability
ds.omop.analysis.get(): Get unified analysis catalog entry metadata
ds.omop.analysis.list(): List unified analysis catalog entries
ds.omop.analysis.run(): Run a unified analysis catalog entry
ds.omop.bind_rows(): Row-bind two schema-identical server-side omop.table data frames
ds.omop.cdm.source(): Get the CDM source description from each server
ds.omop.cdm.version(): Get the CDM version reported by each server
ds.omop.code(): Get the R code that produced a result
ds.omop.cohort.combine(): Combine two cohorts with set operations
ds.omop.cohort.create(): Create a cohort from a structured specification
ds.omop.cohort.definition(): Get a cohort definition by ID
ds.omop.cohort.from_table(): Build a cohort from the persons in a server-side omop.table symbol
ds.omop.cohort.list(): List available cohort definitions
ds.omop.cohort.ref(): Create a cohort reference for the plan DSL (client-only)
ds.omop.column.stats(): Get column-level statistics
ds.omop.columns(): List columns in a table
ds.omop.comorbidity(): Disclosure-safe two-by-two comorbidity (person co-occurrence)
ds.omop.compare(): Compare schemas across servers
ds.omop.concept.ancestors(): Get a concept's ancestors and descendants (hierarchy)
ds.omop.concept.descendants(): Get descendant concepts via the concept_ancestor table
ds.omop.concept.drilldown(): Get concept drilldown profile
ds.omop.concept.expand(): Expand a concept set to a full list of concept IDs
ds.omop.concept.list(): Browse the concept catalog with pagination
ds.omop.concept.locate(): Locate concept across all CDM tables
ds.omop.concept.lookup(): Look up OMOP concepts by ID
ds.omop.concept.prevalence(): Get concept prevalence for a table
ds.omop.concept.relationships(): Get the relationships of one or more concepts
ds.omop.concept.search(): Search for OMOP concepts by name
ds.omop.concept.set(): Build a concept set specification (client-only)
ds.omop.concept.summary(): Summarise a value column scoped to one concept of one table
ds.omop.concept.synonyms(): Get the synonyms of one or more concepts
ds.omop.connect(): Connect to an OMOP CDM resource on DataSHIELD servers
ds.omop.copy_code(): Copy reproducible R code to clipboard
ds.omop.crosstab(): Disclosure-safe two-way cross-tabulation
ds.omop.date.counts(): Get record counts by time period
ds.omop.disclosure.settings(): Inspect the active disclosure thresholds on each server
ds.omop.disconnect(): Disconnect an OMOP session
ds.omop.distribution(): Continuous-value distribution over a cohort, in one call
ds.omop.domain.coverage(): Get cross-table domain coverage
ds.omop.dp.release(): Request a sticky privacy release
ds.omop.dp.status(): Inspect sticky privacy-release services
ds.omop.filter(): Filter the rows of a server-side omop.table data frame
ds.omop.joins(): Get the join relationship graph
ds.omop.login(): Log in and open an OMOP CDM session in one call
ds.omop.merge(): Merge two server-side omop.table data frames on the person key
ds.omop.meta.effect_estimate(): Meta-analyze a comparative effect estimate across databases (evidence synthesis)
ds.omop.missingness(): Get missingness rates for columns
ds.omop.ohdsi.results(): Query an OHDSI result table
ds.omop.ohdsi.status(): Check OHDSI result tool availability
ds.omop.ohdsi.summary(): Get OHDSI tool summary
ds.omop.ohdsi.tables(): List discovered OHDSI result tables
ds.omop.plan(): Create a new extraction plan
ds.omop.plan.baseline(): Add a baseline demographics output to the plan
ds.omop.plan.cohort(): Set a cohort filter on the plan
ds.omop.plan.cohort_membership(): Add a cohort membership output to the plan
ds.omop.plan.concept_dictionary(): Add a concept dictionary output to the plan
ds.omop.plan.events(): Add an event-level extraction to the plan
ds.omop.plan.execute(): Execute a plan and create server-side tables
ds.omop.plan.features(): Add feature extraction with feature specifications
ds.omop.plan.harmonize(): Harmonize a plan for multi-server execution
ds.omop.plan.intervals(): Add an intervals (long) output to the plan
ds.omop.plan.load(): Load an extraction plan from JSON or YAML
ds.omop.plan.options(): Set plan-wide options
ds.omop.plan.outcome(): Add an outcome extraction (convenience wrapper)
ds.omop.plan.person_level(): Add cardinality-safe person-level tables to the plan
ds.omop.plan.person_period(): Add a regular episode-by-period panel to an extraction plan
ds.omop.plan.preview(): Preview a plan (server-side dry run)
ds.omop.plan.save(): Save an extraction plan to JSON or YAML
ds.omop.plan.survival(): Add a survival (time-to-event) output to the plan
ds.omop.plan.temporal_covariates(): Add a temporal (time-binned) covariates output to the plan
ds.omop.plan.validate(): Validate an extraction plan
ds.omop.prevalence(): Covariate prevalence over a cohort, in one call
ds.omop.query.exec(): Execute a query template (DEPRECATED)
ds.omop.query.get(): Get query template details (DEPRECATED)
ds.omop.query.list(): List available query templates (DEPRECATED)
ds.omop.query.pool(): Pool query template results across servers
ds.omop.querylibrary.sticky.release(): Release a pinned QueryLibrary sticky redesign
ds.omop.safe.cutpoints(): Get safe numeric cutpoints for a column
ds.omop.safe.filter.measurement(): Create a safe population filter for a numeric measurement interval
ds.omop.safe.filter.value(): Create a safe numeric value filter using server-computed bins
ds.omop.select(): Keep a subset of columns of a server-side omop.table data frame
ds.omop.snapshot(): Get a full schema snapshot
ds.omop.status(): Get OMOP session status
ds.omop.table.stats(): Get table-level statistics
ds.omop.tables(): List tables in the OMOP CDM database
ds.omop.value.counts(): Get value frequencies for a column
ds.omop.value.histogram(): Get a disclosure-safe numeric histogram
ds.omop.value.quantiles(): Get disclosure-safe numeric quantiles
ds.omop.vocab.classes(): List the concept classes available on each server
ds.omop.vocab.domains(): List the domains available on each server
ds.omop.vocab.vocabularies(): List the vocabularies available on each server
omop.date_handling(): Build a date handling specification
omop.feature.abnormal_high(): Create an abnormal-high count feature specification
omop.feature.abnormal_low(): Create an abnormal-low count feature specification
omop.feature.boolean(): Create a binary (presence/absence) feature specification
omop.feature.count(): Create an event count feature specification
omop.feature.cv_value(): Create a coefficient of variation feature specification
omop.feature.drug_duration(): Create a drug duration feature specification
omop.feature.duration_sum(): Create a duration sum feature specification
omop.feature.first_value(): Create a first-recorded-value feature specification
omop.feature.gap_max_days(): Create a maximum gap (days) feature specification
omop.feature.gap_mean_days(): Create a mean gap (days) feature specification
omop.feature.latest_value(): Create a most-recent-value feature specification
omop.feature.max_value(): Create a maximum value feature specification
omop.feature.mean_value(): Create a mean value feature specification
omop.feature.min_value(): Create a minimum value feature specification
omop.feature.n_distinct(): Create a distinct concept count feature specification
omop.feature.sd_value(): Create a standard deviation feature specification
omop.feature.slope_value(): Create a slope (linear trend) feature specification
omop.feature.sum_value(): Create a sum value feature specification
omop.feature.time_since(): Create a time-since-event feature specification
omop.temporal(): Build a temporal filtering specification
omop_filter() omop_filter_sex() omop_filter_age() omop_filter_age_group() omop_filter_cohort() omop_filter_has_concept() omop_filter_date_range() omop_filter_value() omop_filter_value_concept() omop_filter_not_has_concept() omop_filter_concept_count() omop_filter_prior_observation() omop_filter_followup() omop_filter_visit_count() omop_filter_has_measurement() omop_filter_missing_measurement(): Create a filter specification
omop_filter_group(): Create an AND/OR group of filters
omop_index_event(): Define the OMOP event that anchors a longitudinal population
omop_output(): Create an output specification
omop_population(): Create a population node
omop_privacy(): Define a server-owned sticky privacy release
omop_querylibrary_sticky(): Build an executable sticky redesign of an OHDSI QueryLibrary question
omop_querylibrary_sticky_catalog(): List audited sticky redesign mappings for OHDSI QueryLibrary
omop_recipe(): Create an extraction recipe declaratively
omop_variable(): Create a variable specification
omop_variable_age(): Create an age variable
omop_variable_block(): Create a variable block
omop_variable_chads2(): Create a CHADS2 score variable
omop_variable_chadsvasc(): Create a CHA2DS2-VASc score variable
omop_variable_charlson(): Create a Charlson Comorbidity Index variable
omop_variable_cv(): Create a coefficient of variation variable
omop_variable_dcsi(): Create a DCSI score variable
omop_variable_demo_missingness(): Create a demographics missingness variable
omop_variable_drug_duration(): Create a drug duration variable
omop_variable_followup(): Create a followup duration variable
omop_variable_hfrs(): Create an HFRS score variable
omop_variable_n_distinct(): Create a distinct-concept-count variable
omop_variable_obs_duration(): Create an observation duration variable
omop_variable_prior_obs(): Create a prior observation duration variable
omop_variable_sd(): Create a standard deviation variable
omop_variable_sex(): Create a sex (M/F) variable
omop_variable_slope(): Create a slope (linear trend) variable
omop_variable_sum(): Create a sum variable
plot(<omop_plan>): Plot an extraction plan as a dependency graph
print(<dsomop_result>): Print a dsomop_result
print(<omop_filter>): Print an omop_filter
print(<omop_filter_group>): Print an omop_filter_group
print(<omop_output>): Print an omop_output
print(<omop_plan>): Print method for extraction plans
print(<omop_population>): Print an omop_population
print(<omop_recipe>): Print an omop_recipe
print(<omop_variable>): Print an omop_variable
print(<omop_variable_block>): Print an omop_variable_block
recipe_execute(): Execute a recipe: compile to plan and run
recipe_export_circe(): Export a recipe population to an OHDSI Circe cohort expression
recipe_export_json(): Export a recipe to JSON
recipe_export_yaml(): Export a recipe to YAML
recipe_import_circe(): Import an OHDSI Circe cohort expression as a recipe population
recipe_import_json(): Import a recipe from JSON
recipe_import_yaml(): Import a recipe from YAML
recipe_lint(): Lint a recipe for common authoring mistakes (pure client-side)
recipe_load(): Load a recipe from JSON or YAML
recipe_preview(): Preview a recipe on the server
recipe_preview_schema(): Preview the output schema for a recipe
recipe_preview_stats(): Preview aggregate stats for a recipe (without materializing)
recipe_save(): Save a recipe to JSON or YAML
recipe_to_code(): Generate reproducible R code from a recipe
recipe_to_plan(): Convert a recipe to an extraction plan
recipe_validate(): Validate a recipe on the server
summary(<omop_plan>): Summarise an extraction plan