Package index • lrstat

All functions
`BOINTable()`	BOIN Decision Table for Dose-Finding Trials
`ClopperPearsonCI()`	Clopper-Pearson Confidence Interval for One-Sample Proportion
`accrual()`	Number of Enrolled Subjects
`adaptDesign()`	Adaptive Design at an Interim Look
`adaptDesign_multiarm()`	Adaptive Multi-Arm Multi-Stage Design
`adaptDesign_seamless()`	Adaptive Phase 2/3 Seamless Design
`aml`	Acute myelogenous leukemia survival data from the survival package
`assess_phregr()`	Assess Proportional Hazards Assumption Based on Supremum Test
`binary_tte_sim()`	Simulation for a Binary and a Time-to-Event Endpoint in Group Sequential Trials
`caltime()`	Calendar Times for Target Number of Events
`corr_pfs_os()`	Correlation Between PFS and OS Given Correlation Between PD and OS
`covrmst()`	Covariance Between Restricted Mean Survival Times
`dtpwexp()`	Density Function of Truncated Piecewise Exponential Distribution
`errorSpent()`	Error Spending
`exitprob()`	Stagewise Exit Probabilities
`exitprob_multiarm()`	Exit Probabilities for Multi-Arm Multi-Stage Design
`exitprob_seamless()`	Exit Probabilities for Phase 2/3 Seamless Design
`fCERCer()`	Compute conditional error rates
`fCERNewBound()`	Compute new stage-wise bounds after adaptation
`fCERRej()`	Determine stage 2 rejections from conditional error rates
`fCERStageBound()`	Compute stage-wise bounds for multiple testing
`fDefaultWgtmat()`	Default Weight Matrix for All Intersection Hypotheses
`fPCRej()`	Determine stage 2 rejections using p-value combination
`fPCStage1()`	Determine stage 1 rejections for adaptive multiple testing
`fPCStagewise()`	Compute stage-wise local p-values
`fadjpbon()`	Adjusted p-Values for Bonferroni-Based Graphical Approaches
`fadjpdun()`	Adjusted p-Values for Dunnett-Based Graphical Approaches
`fadjpsim()`	Adjusted p-Values for Simes-Based Graphical Approaches
`finthyp()`	Indicator Matrix for All Intersection Hypotheses
`float_to_fraction()`	Converting a decimal to a fraction
`fmodmix()`	Adjusted p-Values for Modified Mixture Gatekeeping Procedures
`fquantile()`	The Quantiles of a Survival Distribution
`fseqbon()`	Group Sequential Trials Using Bonferroni-Based Graphical Approaches
`fstdmix()`	Adjusted p-Values for Standard Mixture Gatekeeping Procedures
`fstp2seq()`	Adjusted p-Values for Stepwise Testing Procedures for Two Sequences
`ftrunc()`	Adjusted p-Values for Holm, Hochberg, and Hommel Procedures
`fwgtmat()`	Weight Matrix for All Intersection Hypotheses
`getADCI()`	Confidence Interval After Adaptation
`getADCI_multiarm()`	Confidence Interval After Adaptation for Multi-Arm Multi-Stage Design
`getADCI_seamless()`	Confidence Interval After Adaptation for Phase 2/3 Seamless Design
`getADRCI()`	Repeated Confidence Interval After Adaptation
`getAccrualDurationFromN()`	Accrual Duration to Enroll Target Number of Subjects
`getBound()`	Efficacy Boundaries for Group Sequential Design
`getBound_multiarm()`	Efficacy Boundaries for Multi-Arm Multi-Stage Design
`getBound_seamless()`	Efficacy Boundaries for Phase 2/3 Seamless Design
`getCI()`	Confidence Interval After Trial Termination
`getCI_multiarm()`	Confidence Interval After Trial Termination for Multi-Arm Multi-Stage Design
`getCI_seamless()`	Confidence Interval After Trial Termination for Phase 2/3 Seamless Design
`getCP()`	Conditional Power for Generic Group Sequential Design
`getCP_multiarm()`	Conditional Power for Multi-Arm Multi-Stage Design
`getCP_seamless()`	Conditional Power for Phase 2/3 Seamless Design
`getDesign()`	Power and Sample Size for Generic Group Sequential Design
`getDesign2()`	Power and Sample Size for Group Sequential Design With Futility Stopping Under Null Hypothesis
`getDesignANOVA()`	Power and Sample Size for One-Way ANOVA
`getDesignANOVAContrast()`	Power and Sample Size for One-Way ANOVA Contrast
`getDesignAgreement()`	Power and Sample Size for Cohen's kappa
`getDesignEquiv()`	Power and Sample Size for Generic Group Sequential Equivalence Design
`getDesignFisherExact()`	Power and Sample Size for Fisher's Exact Test for Two Proportions
`getDesignLogistic()`	Power and Sample Size for Logistic Regression
`getDesignMeanDiff()`	Group Sequential Design for Two-Sample Mean Difference
`getDesignMeanDiffCarryover()`	Power and Sample Size for Direct Treatment Effects in Crossover Trials
`getDesignMeanDiffCarryoverEquiv()`	Power and Sample Size for Equivalence in Direct Treatment Effects in Crossover Trials
`getDesignMeanDiffEquiv()`	Group Sequential Design for Equivalence in Two-Sample Mean Difference
`getDesignMeanDiffMMRM()`	Group Sequential Design for Two-Sample Mean Difference From the MMRM Model
`getDesignMeanDiffXO()`	Group Sequential Design for Mean Difference in 2x2 Crossover
`getDesignMeanDiffXOEquiv()`	Group Sequential Design for Equivalence in Mean Difference in 2x2 Crossover
`getDesignMeanRatio()`	Group Sequential Design for Two-Sample Mean Ratio
`getDesignMeanRatioEquiv()`	Group Sequential Design for Equivalence in Two-Sample Mean Ratio
`getDesignMeanRatioXO()`	Group Sequential Design for Mean Ratio in 2x2 Crossover
`getDesignMeanRatioXOEquiv()`	Group Sequential Design for Equivalence in Mean Ratio in 2x2 Crossover
`getDesignOddsRatio()`	Group Sequential Design for Two-Sample Odds Ratio
`getDesignOddsRatioEquiv()`	Group Sequential Design for Equivalence in Two-Sample Odds Ratio
`getDesignOneMean()`	Group Sequential Design for One-Sample Mean
`getDesignOneMultinom()`	Power and Sample Size for One-Sample Multinomial Response
`getDesignOneProportion()`	Group Sequential Design for One-Sample Proportion
`getDesignOneRateExact()`	Power and Sample Size for One-Sample Poisson Rate Exact Test
`getDesignOneSlope()`	Group Sequential Design for One-Sample Slope
`getDesignOrderedBinom()`	Power and Sample Size for Cochran-Armitage Trend Test for Ordered Multi-Sample Binomial Response
`getDesignPairedMeanDiff()`	Group Sequential Design for Paired Mean Difference
`getDesignPairedMeanDiffEquiv()`	Group Sequential Design for Equivalence in Paired Mean Difference
`getDesignPairedMeanRatio()`	Group Sequential Design for Paired Mean Ratio
`getDesignPairedMeanRatioEquiv()`	Group Sequential Design for Equivalence in Paired Mean Ratio
`getDesignPairedPropMcNemar()`	Group Sequential Design for McNemar's Test for Paired Proportions
`getDesignRepeatedANOVA()`	Power and Sample Size for Repeated-Measures ANOVA
`getDesignRepeatedANOVAContrast()`	Power and Sample Size for One-Way Repeated Measures ANOVA Contrast
`getDesignRiskDiff()`	Group Sequential Design for Two-Sample Risk Difference
`getDesignRiskDiffEquiv()`	Group Sequential Design for Equivalence in Two-Sample Risk Difference
`getDesignRiskDiffExact()`	Power and Sample Size for Exact Unconditional Test for Risk Difference
`getDesignRiskDiffExactEquiv()`	Power and Sample Size for Exact Unconditional Test for Equivalence in Risk Difference
`getDesignRiskRatio()`	Group Sequential Design for Two-Sample Risk Ratio
`getDesignRiskRatioEquiv()`	Group Sequential Design for Equivalence in Two-Sample Risk Ratio
`getDesignRiskRatioExact()`	Power and Sample Size for Exact Unconditional Test for Risk Ratio
`getDesignRiskRatioExactEquiv()`	Power and Sample Size for Exact Unconditional Test for Equivalence in Risk Ratio
`getDesignRiskRatioFM()`	Group Sequential Design for Two-Sample Risk Ratio Based on the Farrington-Manning Score Test
`getDesignSlopeDiff()`	Group Sequential Design for Two-Sample Slope Difference
`getDesignSlopeDiffMMRM()`	Group Sequential Design for Two-Sample Slope Difference From the MMRM Model
`getDesignTwoMultinom()`	Power and Sample Size for Difference in Two-Sample Multinomial Responses
`getDesignTwoOrdinal()`	Power and Sample Size for the Wilcoxon Test for Two-Sample Ordinal Response
`getDesignTwoWayANOVA()`	Power and Sample Size for Two-Way ANOVA
`getDesignUnorderedBinom()`	Power and Sample Size for Unordered Multi-Sample Binomial Response
`getDesignUnorderedMultinom()`	Power and Sample Size for Unordered Multi-Sample Multinomial Response
`getDesignWilcoxon()`	Group Sequential Design for Two-Sample Wilcoxon Test
`getDesign_multiarm()`	Power and Sample Size for Multi-Arm Multi-Stage Design
`getDesign_seamless()`	Power and Sample Size for Phase 2/3 Seamless Design
`getDurationFromNevents()`	Range of Accrual Duration for Target Number of Events
`getNFromNeventsAndFollowup()`	Accrual Duration for Target Number of Events and Follow-up Time
`getNeventsFromHazardRatio()`	Required Number of Events Given Hazard Ratio
`getRCI()`	Repeated Confidence Interval for Group Sequential Design
`hazard_pd()`	Hazard Function for Progressive Disease (PD) Given Correlation Between PD and OS
`hazard_sub()`	Hazard Function for Sub Population
`heart`	Stanford heart transplant data from the survival package
`hedgesg()`	Hedges' g Effect Size
`immdef`	Simulated CONCORDE trial data from the rpsftm package
`ingots`	The binary data from Cox and Snell (1989, pp. 10-11).
`kmdiff()`	Estimate of Milestone Survival Difference
`kmest()`	Kaplan-Meier Estimates of Survival Curve
`kmpower()`	Power for Difference in Milestone Survival Probabilities
`kmpower1s()`	Power for One-Sample Milestone Survival Probability
`kmpowerequiv()`	Power for Equivalence in Milestone Survival Probability Difference
`kmsamplesize()`	Sample Size for Difference in Milestone Survival Probabilities
`kmsamplesize1s()`	Sample Size for One-Sample Milestone Survival Probability
`kmsamplesizeequiv()`	Sample Size for Equivalence in Milestone Survival Probability Difference
`kmstat()`	Stratified Difference in Milestone Survival Probabilities
`liferegr()`	Parametric Regression Models for Failure Time Data
`liver`	The liver data used in SAS PROC PHREG documentation examples.
`logisregr()`	Logistic Regression Models for Binary Data
`lrpower()`	Log-Rank Test Power
`lrpowerequiv()`	Power for Equivalence in Hazard Ratio
`lrsamplesize()`	Log-Rank Test Sample Size
`lrsamplesizeequiv()`	Sample Size for Equivalence in Hazard Ratio
`lrschoenfeld()`	Schoenfeld Method for Log-Rank Test Sample Size Calculation
`lrsim()`	Log-Rank Test Simulation
`lrsim2e()`	Log-Rank Test Simulation for PFS and OS Endpoints
`lrsim2e3a()`	Log-Rank Test Simulation for Two Endpoints (PFS and OS) and Three Arms
`lrsim3a()`	Log-Rank Test Simulation for Three Arms
`lrsim_bmTrtSel()`	Simulation of a seamless phase II/III design with treatment selection based on a short-term endpoint and toxicities
`lrsim_mcpmod()`	Log-Rank Test Simulation for MCPMod Design
`lrsim_multiarm()`	Log-Rank Test Simulation for Multi-Arm Multi-Stage Design
`lrsim_pkTrtSel()`	Simulate the Carreras adaptive seamless design with PK-guided selection
`lrsim_seamless()`	Log-Rank Test Simulation for Phase 2/3 Seamless Design
`lrsimsub()`	Log-Rank Test Simulation for Enrichment Design
`lrstat-package`	Power and Sample Size Calculation for Non-Proportional Hazards and Beyond
`lrstat()`	Number of Subjects Having an Event and Log-Rank Statistics
`lrtest()`	Log-Rank Test of Survival Curve Difference
`mTPI2Table()`	mTPI-2 Decision Table
`mnOddsRatioCI()`	Miettinen-Nurminen Score Confidence Interval for Two-Sample Odds Ratio
`mnRateDiffCI()`	Miettinen-Nurminen Score Confidence Interval for Two-Sample Rate Difference
`mnRateRatioCI()`	Miettinen-Nurminen Score Confidence Interval for Two-Sample Rate Ratio
`mnRiskDiffCI()`	Miettinen-Nurminen Score Confidence Interval for Two-Sample Risk Difference
`mnRiskRatioCI()`	Miettinen-Nurminen Score Confidence Interval for Two-Sample Risk Ratio
`mtpwexp()`	Mean and Variance of Truncated Piecewise Exponential Distribution
`natrisk()`	Number of Subjects at Risk
`nbpower()`	Power for Negative Binomial Rate Ratio
`nbpower1s()`	Power for One-Sample Negative Binomial Rate
`nbpowerequiv()`	Power for Equivalence in Negative Binomial Rate Ratio
`nbsamplesize()`	Sample Size for Negative Binomial Rate Ratio
`nbsamplesize1s()`	Sample Size for One-Sample Negative Binomial Rate
`nbsamplesizeequiv()`	Sample Size for Equivalence in Negative Binomial Rate Ratio
`nbstat()`	Negative Binomial Rate Ratio
`nevent()`	Number of Subjects Having an Event by Calendar Time
`patrisk()`	Probability of Being at Risk
`pbvnorm()`	Distribution Function of the Standard Bivariate Normal
`pevent()`	Probability of Having an Event
`phregr()`	Proportional Hazards Regression Models
`pmvnormr()`	Multivariate Normal Probabilities over a Hyperrectangle
`pordmvnormr()`	Distribution Function for a Normal Order Statistic
`ptpwexp()`	Distribution Function of Truncated Piecewise Exponential Distribution
`pwexpcuts()`	Piecewise Exponential Approximation to a Survival Distribution
`pwexploglik()`	Profile Log-Likelihood Function for Change Points in Piecewise Exponential Approximation
`qmvnormr()`	Equicoordinate Quantiles of the Multivariate Normal Distribution
`qtpwexp()`	Quantile Function of Truncated Piecewise Exponential Distribution
`rawdata`	A simulated time-to-event data set with 10 replications
`rdsim_multiarm()`	Risk Difference Simulation for Multi-Arm Multi-Stage Design
`rdsim_seamless()`	Risk Difference Simulation for Phase 2/3 Seamless Design
`remlOddsRatio()`	REML Estimates of Individual Proportions With Specified Odds Ratio
`remlRateDiff()`	REML Estimates of Individual Rates With Specified Rate Difference
`remlRateRatio()`	REML Estimates of Individual Rates With Specified Rate Ratio
`remlRiskDiff()`	REML Estimates of Individual Proportions With Specified Risk difference
`remlRiskRatio()`	REML Estimates of Individual Proportions With Specified Risk Ratio
`repeatedPValue()`	Repeated p-Values for Group Sequential Design
`residuals_liferegr()`	Residuals for Parametric Regression Models for Failure Time Data
`residuals_phregr()`	Residuals for Proportional Hazards Regression Models
`riskDiffExactCI()`	Exact Unconditional Confidence Interval for Risk Difference
`riskDiffExactPValue()`	P-Value for Exact Unconditional Test of Risk Difference
`riskRatioExactCI()`	Exact Unconditional Confidence Interval for Risk Ratio
`riskRatioExactPValue()`	P-Value for Exact Unconditional Test of Risk Ratio
`rmdiff()`	Estimate of Restricted Mean Survival Time Difference
`rmest()`	Estimate of Restricted Mean Survival Time
`rmpower()`	Power for Difference in Restricted Mean Survival Times
`rmpower1s()`	Power for One-Sample Restricted Mean Survival Time
`rmpowerequiv()`	Power for Equivalence in Restricted Mean Survival Time Difference
`rmsamplesize()`	Sample Size for Difference in Restricted Mean Survival Times
`rmsamplesize1s()`	Sample Size for One-Sample Restricted Mean Survival Time
`rmsamplesizeequiv()`	Sample Size for Equivalence in Restricted Mean Survival Time Difference
`rmst()`	Restricted Mean Survival Time
`rmstat()`	Stratified Difference in Restricted Mean Survival Times
`rtpwexp()`	Random Number Generation Function of Truncated Piecewise Exponential Distribution
`runShinyApp_lrstat()`	Run Shiny App
`sexagg`	Urinary tract infection data from the logistf package
`shilong`	The randomized clinical trial SHIVA data in long format from the ipcwswitch package
`simon2stage()`	Simon's Two-Stage Design
`simonBayesAnalysis()`	Analysis of Simon's Bayesian Basket Trials
`simonBayesSim()`	Simulation of Simon's Bayesian Basket Trials
`six`	The repeated measures data from the "Six Cities" study of the health effects of air pollution (Ware et al. 1984).
`survQuantile()`	Brookmeyer-Crowley Confidence Interval for Quantiles of Right-Censored Time-to-Event Data
`survfit_phregr()`	Survival Curve for Proportional Hazards Regression Models
`svdcpp()`	Singular Value Decomposition of a Matrix
`tobin`	Tobin's tobit data from the survival package
`updateGraph()`	Update Graph for Graphical Approaches
`zph_phregr()`	Assess Proportional Hazards Assumption Based on Scaled Schoenfeld Residuals
`zstatOddsRatio()`	Miettinen-Nurminen Score Test Statistic for Two-Sample Odds Ratio
`zstatRateDiff()`	Miettinen-Nurminen Score Test Statistic for Two-Sample Rate Difference
`zstatRateRatio()`	Miettinen-Nurminen Score Test Statistic for Two-Sample Rate Ratio
`zstatRiskDiff()`	Miettinen-Nurminen Score Test Statistic for Two-Sample Risk difference
`zstatRiskRatio()`	Miettinen-Nurminen Score Test Statistic for Two-Sample Risk Ratio

Reference

All functions