Package index • drcHelper

All functions

DixonQ: Dixon's outlier test critical Q table

ECx_rating(): Rate Effect Concentration Estimates Based on Normalized Width

ED(<plus>) ED(<ZG>): Calculating ED following the regulatory ED definition.

NTA_Ar_ext_mortality_expected: Expected outcome of pre-processing NTA_Ar_ext mortality

NTP_example: NTP_example data

NTP_example_rate: Expected processed data from the NTP_example

NTP_example_rate_expected: Expected outcome of NTP

RSCABK(): Runs the kth slice of RSCABS

SpearmanKarber_modified(): Spearman-Karber Estimation with Modified Handling for Control Mortality

Tarone.test(): Tarone's Z Test

Tarone.trend.test(): Tarone's test for overdispersion accounting for trend

addECxCI(): adding ECx estimation and interval to the model output plot

aggregate_from_individual_simple(): Aggregate Individual Fish Records to Summarized Format (simple without tidyverse version)

aggregate_from_individual_tidy(): Aggregate Individual Fish Records to Summarized Format (tidyverse version)

analyze_SK(): Unified Spearman-Karber Analysis Function

backCalcSE(): Back Calculate Standard Error from Lognormal Parameters

broom_dunnett(): Standardize Dunnett Test Results

broom_williams(): Standardize Williams Test Results

calcNW(): Calculate Normalized Width for Effect Concentration Estimates

calcSteepnessOverlap(): Steepness and overlap calcuation

calcTaronesTest(): Tarones test for Stratified OR (ClinStats version)

calculate_noec_rstatix(): Calculate NOEC Using Many-to-one Pairwise Tests

calpha.test(): C(alpha) test from the epiphy package.

cochranArmitageTrendTest(): Cochran-Armitage Trend Test for Binomial Data

collembola_juveniles: Fake data from collembola juveniles

compare_phi_methods(): Compare phi estimation methods (FIXED)

compare_tarone_scoring(): Compare Tarone trend tests across different scoring methods

compare_to_control_fisher(): Perform Fisher's Exact Test Comparing Each Level to Control

complete_trend_analysis(): Perform complete overdispersion and trend analysis (CORRECTED)

comprehensive_phi_comparison(): Compare phi estimates across different scoring methods and estimation methods

compute_mdd_williams(): Calculate MDD% for a Williams Test Result

contEndpoint(): get Endpoint for continuous data according to results of a series of tests

convert2Score(): Convert Values to Scores

convert_fish_data(): Convert Between Aggregated and Individual Fish Data

create_contingency_table(): Create Contingency Table from Count Data

create_summary_table(): Create a summary table for manuscript/report

dat_bcs1: Fake data as an example of PVI data

dose.p.glmmPQL(): Calculate Dose Probability for GLMM using PQL

drcCompare(): Compare Dose-Response Models Using Multiple Criteria

williamsTestLookUpTable test_cases_data test_cases_res dat_shallow dat_steep dat_medium dat_noED50: Williams Test Lookup Table

dunn_test(): Dunn's Multiple Comparison Test

dunnett_test(): Conduct Dunnett Test with Various Model Specifications

estimate_phi_with_scoring(): Estimate overdispersion parameter using consistent scoring (CORRECTED)

exampleHistData: exampleHistData from StatCharrms

expand_to_individual_simple(): Expand Aggregated Fish Data to Individual Records (simple without tidyverse version)

expand_to_individual_tidy(): Expand Aggregated Fish Data to Individual Records (tidyverse version)

getComparison(): Function to get the comparison groups for Williams test or other.

getEC50(): Get the EC50 Estimate from a Model

getEndpoint(): Obtain Endpoint (NOEC) according to a series of p-values

getLineContrast(): Calculate Linear Contrast for Treatment Levels

getModelName(): Get Model Name and Description

getQuadContrast(): Calculate Quadratic Contrast for Treatment Levels

get_CA_Z(): Calculate Cochran-Armitage Trend Test Z-Statistic

get_RS_adj_val(): Calculate Rao-Scott Adjusted Values for Clustered Binary Data

getwilliamRes(): get from william res accept/reject

hamilton: This is hamilton data

invlogxp(): inverse transformation of logxp

log_message(): Adding detailed logging

logxp(): Helper function for scaling x-axis

many_to_one_fisher_test(): Many-to-One Pairwise Fisher's Exact Test

metaldata: Data from heavy metal mixture experiments (drcData)

monotonicityTest(): Testing Monotonicity

mselect.ED(): ECx calculation together with normalized width proposed by EFSA SO.

mselect.plus() mselect.ZG(): added functionality for mselect

oecd201: An example dataset from study type OECD 201

oscillating_response(): Generate Oscillating Response Pattern

pavaMean(): Calculate Means Using the Pool Adjacent Violators Algorithm (PAVA)

perform_groupwise_tarone(): Perform Tarone test within each dose group

plot(<StepDownRSCABS>): Plot method for StepDownRSCABS objects

plot(<dunnett_test_result>): Plot method for dunnett_test_result objects

plot(<modList>): Plot a list of models together.

plot_edList(): Plot the ECx estimation and confidence intervals from the list of models.

prelimPlot1(): Preliminary Plot 1 for Dose Response Data

prelimPlot2(): Preliminary Plot 2 for Dose Response Data, with x continuous.

prelimPlot3(): Preliminary Plot 3 for Dose Response Data

prelimSummary(): Preliminary Summary of Dose Response Data

prepDataRSCABS(): Prepares data for an RSCABS analysis

print(<RSCABS>): Printing method for run_all_threshold_tests results

print(<StepDownRSCABS>): Print method for StepDownRSCABS objects

print(<TaroneTrendTest>): Print method for TaroneTrendTest with tabular output

print(<completeTrendAnalysis>): Print method for complete trend analysis (UPDATED)

print(<drcComp>): Print Method for drcComp Objects

print(<dunn_test_result>): Print method for dunn_test_result

print(<dunnett_test_result>): Print method for dunnett_test_result objects

print(<stepDownTrendBinom>): Print Method for stepDownTrendBinom Objects

pvi_example: Fake data as an example of PVI data

quantal_dat_nested: Data from Acute Studies

rankTransform(): Rank Transform Data Using Blom's Method

reshape_drcData(): Reshape the wide data to long data

runRSCABS(): Run RSCABS test (DEPRECATED)

run_RSCA(): Run Rao-Scott Adjusted Cochran-Armitage Trend Test

run_all_threshold_tests(): Run Rao-Scott Adjusted Cochran-Armitage Trend Tests for All Thresholds

run_threshold_RSCA(): Run Rao-Scott Adjusted Cochran-Armitage Trend Test for a Specific Injury Threshold

simDRdata(): Wrapper around rdrm

simplifyTreatment(): Resolve the excel datasheet number issues

simulate_dose_response(): Simulate Hierarchical Dose-Response Data with Inhomogeneous Variance

stepDownRSCABS(): Performs the step down aspect of RSCABS

stepDownTrendTestBinom(): Step-down Cochran-Armitage trend test with consistent scoring

stepKRSCABS(): plotRSCABS

step_down_RSCABS(): Perform Step-Down Rao-Scott Adjusted Cochran-Armitage Trend Test Procedure

summary(<StepDownRSCABS>): Summary method for StepDownRSCABS objects

summaryZG(): Summary Williams Test results.

tarone_with_trend_removal(): Internal function to perform Tarone test with trend removal and calculate phi

test_overdispersion(): Function to test for overdispersion in binomial data using glm approach

treatment2dose(): Change Treatment groups to numerical dose

tsk(): Trimmed Spearman-Karber Method by brsr

tsk(<data.frame>): TSK Analysis for Data Frame Input

tsk(<numeric>): TSK Analysis for Numeric Input

tsk_auto(): Auto-trimmed TSK Analysis

williamsTest_JG(): Williams Test from the StatCharrms Package