stenR0.6.9 package

Standardization of Raw Discrete Questionnaire Scores

attach_scales

Attach additional StandardScale to already created ScoreTable

check_score_between

Pick up standarized value from ScoringTable

CombScaleSpec

Combined Scale Specification

CompScoreTable

R6 class for producing easily re-computable ScoreTable

default_scales

Default Standard Scales

export_ScaleSpec

Export scale specification

export_ScoringTable

Export ScoringTable

extract_observations

Extract observations from data

FrequencyTable

Create a FrequencyTable

GroupAssignment

Assign to groups based on GroupConditions

GroupConditions

Conditions for observation grouping

GroupedFrequencyTable

Create GroupedFrequencyTable

GroupedScoreTable

Create GroupedScoreTable

handle_retain

Handle retain columns

import_ScaleSpec

Import scale specification

import_ScoringTable

Import ScoringTable

intersect_GroupAssignment

Intersect two GroupAssignment

is_stenR_classes

Checkers for stenR S3 and R6 classes

mockNAtable

Mockup NA table

normalize_score

Normalize raw scores

normalize_scores_df

Normalize raw scores for multiple variables

normalize_scores_grouped

Normalize scores using GroupedFrequencyTables or GroupedScoreTables

normalize_scores_scoring

Normalize scores using ScoringTables

plot.GroupedFrequencyTable

Gerenic plot of the GroupedFrequencyTable

plot.GroupedScoreTable

Gerenic plot of the GroupedScoreTable

qualify_to_groups

Qualify observations to groups for normalization

ScaleSpec

Scale Specification object

ScoreTable

Create a ScoreTable

ScoringTable

Create ScoringTable

SimFrequencyTable

Generate FrequencyTable using simulated distribution

StandardScale

Specify standard scale

strip_ScoreTable

Revert the ScoreTable back to FrequencyTable object.

sum_items_to_scale

Sum up discrete raw data

verify_GC_for_ST

Internal function to verify the provided conditions with conditions av...

An user-friendly framework to preprocess raw item scores of questionnaires into factors or scores and standardize them. Standardization can be made either by their normalization in representative sample, or by import of premade scoring table.