Package index • clinicalsignificance

Core Analysis Functions

The starting point for your workflow. Use these functions to perform the core analyses of clinical significance.

cs_anchor(): Anchor-Based Analysis of Clinical Significance
cs_percentage(): Percentage-Change Analysis of Clinical Significance
cs_distribution(): Distribution-Based Analysis of Clinical Significance
cs_statistical(): Statistical Analysis of Clinical Significance
cs_combined(): Combined Analysis of Clinical Significance

Visualize and Summarize Results

Methods to visualize and summarize the results of your analyses.

plot(<cs_anchor_group_between>): Plot an Object of Class cs_anchor_group_between
plot(<cs_anchor_group_within>): Plot an Object of Class cs_anchor_group_within
plot(<cs_anchor_individual_within>): Plot an Object of Class cs_anchor_individual_within
plot(<cs_combined>): Plot an Object of Class cs_combined
plot(<cs_distribution>): Plot an Object of Class cs_distribution
plot(<cs_percentage>): Plot an Object of Class cs_percentage
plot(<cs_statistical>): Plot an Object of Class cs_statistical
summary(<cs_anchor_group_between>): Summary Method for the Anchor-Based Approach for Groups (Between)
summary(<cs_anchor_group_within>): Summary Method for the Anchor-Based Approach for Groups (Within)
summary(<cs_anchor_individual_within>): Summary Method for the Anchor-Based Approach
summary(<cs_combined>): Summary Method for the Combined Approach
summary(<cs_distribution>): Summary Method for the Distribution-Based Approach
summary(<cs_percentage>): Summary Method for the Percentage-Change Approach
summary(<cs_statistical>): Summary Method for the Statistical Approach
print(<cs_anchor_group_between>): Print Method for the Anchor-Based Approach for Groups (Between)
print(<cs_anchor_group_within>): Print Method for the Anchor-Based Approach for Groups (Within)
print(<cs_anchor_individual_within>): Print Method for the Anchor-Based Approach for Individuals
print(<cs_combined>): Print Method for the Combined Approach
print(<cs_distribution>): Print Method for the Distribution-Based Approach
print(<cs_percentage>): Print Method for the Percentange-Change Approach
print(<cs_statistical>): Print Method for the Statistical Approach

Extractor Functions

Helper functions to extract specific information and data from the analysis objects.

cs_get_augmented_data(): Extract Augmented Data from a cs_analysis Object
cs_get_cutoff(): Get Used Cutoff And Type From A cs_analysis Object
cs_get_cutoff_descriptives(): Get Descriptives Used In The Cutoff Calculation
cs_get_data(): Get Data From A cs_analysis Object
cs_get_model(): Get The HLM Model From A cs_analysis Object
cs_get_n(): Get Number Of Participants From A cs_analysis Object
cs_get_reliability(): Get Reliability Of A cs_analysis Object
cs_get_summary(): Get A Summary Table From A cs_analysis Object

Included Datasets

Example datasets for demonstrating and testing the package functions.

jacobson_1989: Marital Therapy Data
claus_2020: Placebo Amplification Data
anxiety: Anxiety Data
anxiety_complete: Anxiety Data (Complete)
antidepressants: Antidepressant Data
hechler_2014: Chronic Pain Data
columbo: Fictional "Columbo's Detectives" Data with Missing Values
garden_club: Fictional "Garden Club" Pre-Post Intervention Data
garden_club_sensitive: Fictional "Garden Club" Data for MID Sensitivity Analysis
trackmania: Fictional "Trackmania" Racing Data for Interrupted Time-Series