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| bcgVaccineData | Example: Setting up the BCG-data set |
| boxBias | Plotting performance: Box plots for bias |
| boxByConfidence | Plotting performance: Box plots for target value confidence-coverage |
| boxByMethod | Plotting performance: Box plots for target value confidence-coverage |
| boxByType | Plotting performance: Box plots for target value confidence-coverage |
| boxMSE | Plotting performance: Box plots for mean squared error |
| boxSD | Plotting performance: Box plots for standard deviation |
| cbbPalette | Colour palettes for colour blind people |
| cbgPalette | Colour palettes for colour blind people |
| collectAllExperiments | Running a computer experiment - Collect all the results |
| collectExperiments | Running a computer experiment - Collect specific results |
| designB | Design: Binomial responses |
| designD | Design: Gaussian responses (unknown heteroscedasticity) |
| designY | Design: Gaussian responses (known heteroscedasticity) |
| dvec | Data generation: Sampling data of clinical trials |
| experimentD | Running a computer experiment |
| experimentY | Running a computer experiment |
| formulaL | Regression coefficients: formulaL |
| formulaR | Regression coefficients: formulaR |
| hConfidence | Inference: Based on methods of moments and maximum likelihood. |
| hEstimates | Point estimates: For the heterogeneity parameter |
| intervalEstimates | Interval estimates: For the regression coefficients |
| joinPivotalCoefficients | Pivotal distributions: Extract pivots for regression coefficients |
| joinPivotalHeterogeneity | Pivotal distributions: Extract pivots for heterogeneity |
| lenBoxByMethod | Plotting performance: Box plot of mean width |
| lenBoxByType | Plotting performance: Box plot of mean width |
| lenDenByMethod | Plotting performance: Density estimate of mean width |
| lenDenByType | Plotting performance: Density estimate of mean width |
| makeConfInt | Interval estimates: Generic function |
| makeConfInts | Interval estimates: Generic function |
| metagen | Inference: Analysis of the data set |
| metagenEmpty | Inference: Empty skeleton |
| metagenGeneralised | Inference: Based on generalised inference principles. |
| metareg | Inference: Based on methods of moments and maximum likelihood. |
| performance | Running a computer experiment |
| performanceConfH | Running a computer experiment: Adding performance measures |
| performanceConfR | Running a computer experiment: Adding performance measures |
| performancePointH | Running a computer experiment: Adding performance measures |
| performancePointR | Running a computer experiment: Adding performance measures |
| pfunc | The p_delta(eta) function. |
| pivotalStream | Steams of pivotal quantities of the regression coefficient |
| plotCoefficientInterval | Plot pivots: Interval estimates of the heterogeneity |
| plotDensityH | Pivotal distributions: Plot pivotal distribution of heterogeneity |
| plotDensityH2 | Pivotal distributions: Plot pivot density of the heterogeneity |
| plotDensityIntercept | Pivotal distributions: Plot pivotal distribution of regression coefficients |
| plotDensityIntercept2 | Pivotal distributions: Plot pivotal distribution of regression coefficients |
| plotDensitySlope | Pivotal distributions: Plot pivotal distribution of regression coefficients |
| plotDensitySlope2 | Pivotal distributions: Plot pivotal distribution of regression coefficients |
| plotHeterogeneityInterval | Plot pivots: Interval estimates of the heterogeneity |
| plotIntervalEstimates | Example: Plotting interval estimates |
| plotStudyForest | Example: Plotting a forest plot of a data frame |
| plotStudyQfuncPfunc | Example: Plotting the q- and p-function from the dissertation |
| plotStudySizes | Example: Plotting study sizes |
| plotStudyUnbalance | Example: Plotting study unbalances in group assignments |
| qfunc | The q_delta(tau) function. |
| rB | Data generation: Log-risk-ration of a binomial-Gaussian model |
| rBinomGauss | Data generation: Sampling data of clinical trials |
| rD | Data generation: Gaussian-Gaussian model |
| regressionEstimates | Point estimates: For the regression coefficients |
| render | Render plot: To PDF |
| renderSVG | Render plot: To SVG |
| rY | Data generation: Gaussian-Gaussian model |
| sctBias | Plotting performance: Scatter plots against heterogeneity |
| sctMSE | Plotting performance: Scatter plots against heterogeneity |
| sctSD | Plotting performance: Scatter plots against heterogeneity |
| sctVersusC | Plotting performance: Scatter plot against heterogeneity |
| sctVersusH | Plotting performance: Scatter plot against heterogeneity |
| sdmByMethod | Plotting performance: Scatter plot against heterogeneity |
| sdmByType | Plotting performance: Scatter plot against heterogeneity |
| sdsByMethod | Plotting performance: Scatter plot against heteroscedasticity |
| sdsByType | Plotting performance: Scatter plot against heteroscedasticity |
| setupExperiment | Running a computer experiment in batch mode |
| yvec | Data generation: Sampling data of clinical trials |