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CRAN - Package clinfun. clinfun: Clinical Trial Design and Data Analysis Functions. Utilities to make your clinical collaborations easier if not fun. It contains functions for designing studies such as Simon 2-stage and group sequential designs and for data analysis such as Jonckheere-Terpstra test and estimating survival quantiles. Version:
Functions in clinfun (1.1.5) pselect. Probability of selection under pick the winner rule. roc.perm.test. Permutation test to compare ROC curve. toxbdry. Stopping rule for toxicity/futility monitoring. twostage.admissible. Admissible design options between Minimax and Optimal.
Utilities to make your clinical collaborations easier if not fun. It contains functions for designing studies such as Simon 2-stage and group sequential designs and for data analysis such as Jonckheere-Terpstra test and estimating survival quantiles.
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- Kendall’s tau-b estimate
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- Nonparametric area under the ROC curve
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tol ... whether continuity correction is used for sample size calculation as in Casagrande, Pike & Smith. Default is to use it. tolerance level for multivariate normal probability computation. additional options passed on the pmvnorm function. The futility boundary is not returned when delta.fb is not specified i.e. stopping for futility is not req...
Calculates the Kendall’s tau-b. ktau(x, y) x first variable y second variable
ktau computes the same quantity as cor(x, y, method="kendall"). It uses a faster algorithm than pairwise comparisons used by cor.
Calculates the operating characteristics of a two-stage boundary.
oc.twostage.bdry returns the type I and II error rates as well as the probability of early temination and expected sample size under pu for a specific boundary. permlogrank Permutation version of survdiff
Small sample survdiff using permutation reference distributions.
nperm number of permutations for the reference distribution formula, data, subset, na.action, rho see survdiff for details
permlogrank is the permutation version of k-sample survdiff. see survdiff in survival package for details.
Functions to calculate the power of rank tests for animal studies.
Computes the nonparametric area under the ROC curve and its variance based on U-statistic theory (DDCP). roc.area.test(markers, status) ## S3 method for class 'roc.area.test' print(x, ...) markers The marker values for each subject. If there are more than one markers then this should be a matrix. status x ... binary disease status indicator object ...
These functions can be used for nonparametric analysis of ROC curves.
The relevant functions are , and . See the individual roc.curve roc.area.test roc.perm.test functions for usage details. toxbdry Stopping rule for toxicity/futility monitoring
Computes a stopping rule and its operating characteristics for toxicity monitoring based repeated significance testing.
pLo rLo pHi rHi n r the toxicity rate that is acceptable. baseline (null) response rate. the toxicity rate that is too high and hence unacceptable. desirable response rate. Stop when it is too unlikely. vector of times (sample size) when toxicty/response is monitored. vector of maximum acceptable toxicities (non-responders for futility) corre-spond...
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The goal of Simon’s two-stage design is to assess the efficacy of a treatment while minimizing the number of patients exposed to an ineffective treatment. The trial begins by enrolling n1 patients in stage 1. If ≤ r1 responses are observed, then early termination occurs, at which point the treatment is not recommended.
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