Man pages for gsearly
Creates Group Sequential Trial Designs when Early Outcomes are Available
| corrExp | Exponential correlation matrix |
| corrUnif | Uniform correlation matrix |
| dataOrder | Order a data frame by subject and ordered time variable |
| expectSampsize | Expected sample size for a gsearly model |
| fixedSampsize | Fixed model sample size for a gsearly model |
| gsearlyFit | Fit a generalized least squares model |
| gsearlyModel | Model based estimates of sample size and power for group... |
| gsearly-package | Group sequential designs with early outcomes |
| gsearlySimulate | Simulates data for a previously fitted gsearly model |
| gsearlyUser | User input estimates of sample size and power for group... |
| modelParameters | Estimates model parameters from raw data |
| plotBoundary | A boundary plot for a gsearly model |
| plot.gsearly | Plot a gsearly model |
| plotInform | An information plot for a gsearly model |
| plotPower | A power plot for a gsearly model |
| plotRecruit | A recruitment plot for a gsearly model |
| print.gsearly | Print a gsearly model |
| print.summary.gsearly | Print a gsearly model summary |
| qol | Quality of life index for patients with knee pain |
| roundInterims | Round a gsearly design interim sample size to integer values |
| simdataExtract | Extract simulated data for a single trial |
| summary.gsearly | Summarise a gsearly model |
| tfuStandard | Standardize follow-up times |
