gsDesignSkills

Guide users through classical group sequential trial design using the gsDesign R package. Use this skill when the user asks about: group sequential boundaries, spending functions (sfLDOF, sfHSD, sfPoints), sample size for time-to-event or binomial trials, gsDesign objects, plotting group sequential bounds, gsSurvPower for power computation, or harm bounds (test.type 7/8).

Guide users through next-generation group sequential design using the gsDesign2 R package. Use this skill when the user asks about: gs_design_ahr, gs_power_ahr, gs_update_ahr, sequential_pval, average hazard ratio designs, non-proportional hazards, piecewise enrollment/failure rates, spending time, or information fraction computation.

Guide users through clinical trial simulation using the simtrial R package. Use this skill when the user asks about: simulating survival trials, simfix, sim_pw_surv, cutting data at calendar or event times, weighted logrank tests, MaxCombo tests, or simulation-based power.

Guide users through classical group sequential trial design using the gsDesign R package. Use this skill when the user asks about: group sequential boundaries, spending functions (sfLDOF, sfHSD, sfPoints), sample size for time-to-event or binomial trials, gsDesign objects, plotting group sequential bounds, gsSurvPower for power computation, or harm bounds (test.type 7/8).

Guide users through next-generation group sequential design using the gsDesign2 R package. Use this skill when the user asks about: gs_design_ahr, gs_power_ahr, gs_update_ahr, sequential_pval, average hazard ratio designs, non-proportional hazards, piecewise enrollment/failure rates, spending time, or information fraction computation.

Guide users through clinical trial simulation using the simtrial R package. Use this skill when the user asks about: simulating survival trials, simfix, sim_pw_surv, cutting data at calendar or event times, weighted logrank tests, MaxCombo tests, or simulation-based power.

Guide users through group sequential design with graphical multiplicity control using the graphicalMCP and gsDesign2 R packages. Use this skill whenever the user asks about: group sequential designs with multiple hypotheses, graphical multiplicity testing, sequential p-values with gsDesign2, combining graphicalMCP with gsDesign2, clinical trial designs with multiple endpoints and populations, Maurer-Bretz procedures, alpha-spending with multiplicity graphs, or adapting the gMCPLite vignette template. Also trigger when users mention spending time, information fraction, or sequential p-values in the context of group sequential or graphical testing.

Guide users through graphical MCP procedures using the gMCPLite R package (legacy). Use this skill when the user asks about: hGraph for multiplicity graph visualization, gMCP for closed testing, or legacy graphical MCP workflows. For new projects, prefer graphicalMCP.

Guide users through graphical multiple comparison procedures using the graphicalMCP R package. Use this skill when the user asks about: multiplicity graphs, Bonferroni-based procedures, graph_create, graph_test_shortcut, graph_update, transition matrices, alpha reallocation, or closed testing with graphs.

Guide users through sample size calculation, group sequential design, and simulation for clinical trials with negative binomial (recurrent event) outcomes using the gsDesignNB R package. Use this skill when the user asks about: negative binomial sample size, recurrent event trials, overdispersed counts, event gaps, rate ratios, Wald test for count data, seasonal event rates, blinded or unblinded sample size re-estimation, group sequential designs for negative binomial endpoints, or the Zhu-Lakkis method.

Guide users through simulating clinical trials using the illness-death model with response. Use this skill when the user asks about: multi-state models for oncology trials, simulating correlated OS/PFS/ORR endpoints, transition rates between disease states, illness-death model calibration, building ADTTE datasets from simulation, analysis cut date determination, or theoretical survival curves from transition rates.

Guide users through multi-endpoint group sequential trial simulation with multiplicity-controlled testing. Use this skill when the user asks about: simulating trials with OS, PFS, and ORR endpoints, illness-death model simulation with gsDesign bounds, sequential p-values in simulation loops, combining graphicalMCP with gsDesign for simulation-based operating characteristics, cumulative rejection probabilities, or building a full pipeline from design through simulation to multiplicity-adjusted testing.

Guide users through confirmatory adaptive clinical trial design and analysis using the rpact R package. Use this skill when the user asks about: adaptive designs, sample size reassessment, conditional power, inverse normal combination test, Fisher combination test, multi-stage designs, or rpact design objects.

Route natural-language clinical trial design requests into normalized semantic intent, package-specific skills, and recommended gsDesign ecosystem workflows. Use when a request spans multiple trial design concepts, when the right package is unclear, or when Codex needs to map endpoint family, estimand, information, timing, boundaries, multiplicity, adaptation, or simulation requirements to gsDesign, gsDesign2, gsDesignNB, simtrial, graphicalMCP, rpact, wpgsd, illness-death, or related skills.

Define and normalize shared clinical trial design vocabulary for gsDesign ecosystem skills. Use when Codex needs consistent meanings for endpoint family, estimand, hypothesis type, information, timing, boundaries, multiplicity, adaptation, simulation, or other semantic fields before choosing a package workflow.

Guide users through weighted parametric group sequential design using the wpgsd R package. Use this skill when the user asks about: correlated test statistics across hypotheses, generate_bounds, closed_test, correlation matrices for nested populations, or parametric multiplicity adjustment with group sequential designs.

Guide users through graphical multiple comparison procedures using the graphicalMCP R package. Use this skill when the user asks about: multiplicity graphs, Bonferroni-based procedures, graph_create, graph_test_shortcut, graph_update, transition matrices, alpha reallocation, or closed testing with graphs.

Guide users through confirmatory adaptive clinical trial design and analysis using the rpact R package. Use this skill when the user asks about: adaptive designs, sample size reassessment, conditional power, inverse normal combination test, Fisher combination test, multi-stage designs, or rpact design objects.

Guide users through group sequential design with graphical multiplicity control using the graphicalMCP and gsDesign2 R packages. Use this skill whenever the user asks about: group sequential designs with multiple hypotheses, graphical multiplicity testing, sequential p-values with gsDesign2, combining graphicalMCP with gsDesign2, clinical trial designs with multiple endpoints and populations, Maurer-Bretz procedures, alpha-spending with multiplicity graphs, or adapting the gMCPLite vignette template. Also trigger when users mention spending time, information fraction, or sequential p-values in the context of group sequential or graphical testing.

Guide users through simulating clinical trials using the illness-death model with response. Use this skill when the user asks about: multi-state models for oncology trials, simulating correlated OS/PFS/ORR endpoints, transition rates between disease states, illness-death model calibration, building ADTTE datasets from simulation, analysis cut date determination, or theoretical survival curves from transition rates.

Guide users through multi-endpoint group sequential trial simulation with multiplicity-controlled testing. Use this skill when the user asks about: simulating trials with OS, PFS, and ORR endpoints, illness-death model simulation with gsDesign bounds, sequential p-values in simulation loops, combining graphicalMCP with gsDesign for simulation-based operating characteristics, cumulative rejection probabilities, or building a full pipeline from design through simulation to multiplicity-adjusted testing.

Guide users through sample size calculation, group sequential design, and simulation for clinical trials with negative binomial (recurrent event) outcomes using the gsDesignNB R package. Use this skill when the user asks about: negative binomial sample size, recurrent event trials, overdispersed counts, event gaps, rate ratios, Wald test for count data, seasonal event rates, blinded or unblinded sample size re-estimation, group sequential designs for negative binomial endpoints, or the Zhu-Lakkis method.

Guide users through graphical MCP procedures using the gMCPLite R package (legacy). Use this skill when the user asks about: hGraph for multiplicity graph visualization, gMCP for closed testing, or legacy graphical MCP workflows. For new projects, prefer graphicalMCP.

Guide users through weighted parametric group sequential design using the wpgsd R package. Use this skill when the user asks about: correlated test statistics across hypotheses, generate_bounds, closed_test, correlation matrices for nested populations, or parametric multiplicity adjustment with group sequential designs.