Click for interactive map. One Arm Time to Event Simulator. Calculate the probability of one random variable being larger than another.
Outcome-adaptive randomization for clinical trials. Phase I-II dose-pair-finding based on utilities of 4-level ordinal efficacy and toxicity. Wavelet-based functional mixed model software. Beta Binomial Distribution Demo. A learning tool to demonstrate a beta-binomial distribution prior being updated to become a posterior distribution.
A method for detection and quantification of protein spots from 2-D gel electrophoresis images, md anderson cancer center software. Predictive probability interim analysis of clinical trials. Solve for distribution parameters provigil and eating disorder common distributions.
Monitoring toxicity and efficacy in phase II clinical trials. A Bayesian hypothesis test-based method for clinical trials with single arm binary patient outcomes.
Software for designing single arm safety monitoring trials with time-to-event endpoints, md anderson cancer center software. Dose-finding based on toxicity probability intervals.
Monitor single-arm time-to-event trials using Bayes factors. Monitoring multiple outcomes in clinical trials. Tabulate stopping conditions for single-arm time-to-event safety monitoring. Calculates requisite sample size to achieve a specified probability of a confidence interval of at most a specified size.
Exact p-values for 2 by 2 tables. A collection of Fortran routines used in writing statistical software. Double-precision study planning calculations. Parallel phase I and II design. Phase II Predictive Probability. Computes the stopping boundaries for the predictive probability design of a single-arm Phase II study with a binary endpoint. Determines the interaction of two drugs as synergy, additivity, or antagonism.
Software associated with md anderson cancer center software adaptive randomization method using short-term and long-term response. R software for computing the prior effective sample size of a Bayesian normal linear or logistic regession model. Estimation and inference under semiparametric proportional density model. Design and conduct Phase I clinical trials that simultaneously optimizes dose and schedule. Estimate interaction indices and their confidence intervals for assessing multiple drug interactions.
Computes Clopper-Pearson confidence intervals for one-sample binomial and Poisson. Monitors late-onset toxicities in Phase I trials using predicted risks. This software uses the Bayesian chi square test to evaluate goodness of fit for seven common models for right-censored time-to-event data. Toxicity-based dose-finding using the Continual Reassessment Method, md anderson cancer center software. Double precision statistical tables. Dose-finding in a clinical trial using a combination of two agents.
Bivariate extension of the CRM. Affymetrix microarray analysis tool. Power of the exact test for a one-sample multinomial distribution. Library of routines for cumulative distribution functions, their inverses, and other parameters. Confidence interval and tests for one-sample binomial and Poisson.
Accelerated failure time model with log-F distribution. K-stage binomial, one sample. Allele frequency estimation from small-pool PCR data. Library of routines for random number generation. Analysis of covariance, comparison of slopes and intercepts. Event chart for time-to-event data. Calculates the chi-square goodness-of-fit test to a set of frequencies. Routine to numerically invert a monotone function. Calculates a multiple range test for a Kruskal-Wallis one-way analysis of variance md anderson cancer center software ranks.
Calculates a one-way analysis of variance from means and SDs supplied by the user. Calculates a two-way analysis of variance from means and SDs supplied by the user. Calculates a multiple range test for a one-way analysis of variance.
Cumulative normal Gaussian distribution for extreme arguments. Bayesian boundaries for phase II monitoring. Simulation of genotype selection. Backward elimination via repeated data splitting. Computes asymptotic power or sample size for nonlinear models. Single-stage designs for logistic regression when parameter values are uncertain.
Corrections for multiple hypothesis tests. Confidence intervals on the difference between two probabilities.