Package index
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applyQtl() - Filter a Tibble to Obtain Values Outside a QTL
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berrySubject - Data derived and adapted from Berry et al (2011) pp 52-63
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berrySummary - Data adapted from Berry et al (2011) pp 52-63
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cavalryDeaths - The Bortkiewicz cavalry dataset
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createObservedMinusExpectedPlot() - Create an Observed Minus Expected Plot
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createObservedMinusExpectedTable() - Create a data.frame containing the results of an Observed - Expected Analysis
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createObservedOverExpectedPlot() - Create an Observed Over Expected Plot
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createObservedOverExpectedTable() - Create an Observed Over Expected Grid Using the work of Katz et al (1978) calculate acceptable limits for the ratio of two binomial proportions. The Type 1 error rate can be specified, and the limits can be one- or two-sided.
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createQtlBubblePlot() - Create a QTL bubble plot
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createQtlPlot() - Summary Plot of Observed Event Rates/Proportions
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.assertColumnDoesNotExist() - Throw an exception of the given column DOES exist in the given data.frame
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.assertColumnExists() - Throw an exception of the given column DOES NOT exist in the given data.frame
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.autorunJagsAndCaptureOutput() - Fit an MCMC model to a dataset, capture and log JAGS messages
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.columnExists() - Determine if a column, passed using NSE, exists in a data.frame
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.createBinomialInit() - Create a JAGS inits suitable for use with run.jags and autorun.jags
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.createPoissonInit() - Create a JAGS inits suitable for use with run.jags and autorun.jags
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.ensureLimitsAreNamed() - Ensures that a vector or scalar is named according to standard rules
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evaluateCustomQTL() - Apply an arbitrary QTL rule to a tibble
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evaluatePointEstimateQTL() - Compares a scalar statistic derived from the posterior with one or more fixed values
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evaluateProbabilityInRangeQTL() - Evaluates a QTL based on prob(study-level metric lies within a range)
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evaluateSiteMetricQTL() - Evaluates a QTL based on the proportion of site level KRIs within a range
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fitBayesBinomialModel() - Fit an MCMC Binomial Model to site-specific Counts
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fitBayesPoissonModel() - Fit an MCMC Poisson Model to Site-specific Event Rates
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getModelString() - Function to obtain the string that defines the default JAGS model for each data type
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shadeRange() - Shade Areas Under The Curve
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siteRates - A dataset of event rates
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vaLung - The Kalbfleisch and Prentice (1980) VA lung dataset.