Package index
Joint estimation and inference
Build a joint asymptotic covariance across heterogeneous outcome models, and run PATED for prognostic-covariate-adjusted treatment-effect tests.
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jointCovariance() - Fitting Regression Models for Multiple Outcomes and Returning the Matrix of Covariance
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pated() - Prognostic Variables Assisted Treatment Effect Detection
Model specifications
Spec constructors describing how each component model is fit. Pass them as the ... arguments to jointCovariance() or pated().
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glm_() - Creating Objects of Generalized Linear Models
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coxph_() - Creating Objects of Proportional Hazards Regression Model
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logrank_() - Creating Objects of Logrank Test
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gee_() - Creating Objects of Generalized Estimation Equation Model
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mmrm_() - Creating Objects of Mixed Models for Repeated Measures
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km_() - Creating Objects of Kaplan-Meier Curve
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quantile_() - Creating Objects of Group Quantile Differences
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coef(<jointCovariance>) - Extract Model Coefficients
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vcov(<jointCovariance>) - Calculate Variance-Covariance Matrix for a Fitted Model Object
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summary(<jointCovariance>) - Object Summaries
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print(<summary.jointCovariance>) - Title Summarize an Analysis of Multiple Outcomes.
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plot(<pated>) - Plot PATED Analysis Results
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actg - ACTG 320 Clinical Trial Dataset
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indo - Rectal Indomethacin for Prevention of Post-ERCP Pancreatitis
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simulateMoData() - Generating Data for Simulation and Testing