Accuracy Statistic Estimation for Imperfect Gold Standards

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Documentation for package ‘emery’ version 0.5.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

boot_ML	Bootstrap ML accuracy statistic estimation for multi-method data
censor_data	Censor data randomly rowwise
define_disease_state	Define the True disease state of a simulated sample
estimate_ML	Estimate maximum likelihood accuracy statistics by expectation maximization
estimate_ML_binary	Estimate maximum likelihood accuracy statistics by expectation maximization
estimate_ML_continuous	Estimate maximum likelihood accuracy statistics by expectation maximization
estimate_ML_ordinal	Estimate maximum likelihood accuracy statistics by expectation maximization
generate_multimethod_binary	Create data sets which simulate paired measurements of multiple methods
generate_multimethod_continuous	Create data sets which simulate paired measurements of multiple methods
generate_multimethod_data	Create data sets which simulate paired measurements of multiple methods
generate_multimethod_ordinal	Create data sets which simulate paired measurements of multiple methods
MultiMethodMLEstimate-class	S4 object containing the results of multi-method ML accuracy estimates
name_thing	Create unique names for a set of things
plot-method	Create plots from a MultiMethodMLEstimate object
plot_ML	Create plots visualizing the ML estimation process and results.
plot_ML_binary	Create plots visualizing the ML estimation process and results.
plot_ML_continuous	Create plots visualizing the ML estimation process and results.
plot_ML_ordinal	Create plots visualizing the ML estimation process and results.
pollinate_ML	Generate seed values for EM algorithm
pollinate_ML_binary	Generate seed values for EM algorithm
pollinate_ML_continuous	Generate seed values for EM algorithm
pollinate_ML_ordinal	Generate seed values for EM algorithm
show-method	Show a MultiMethodMLEstimate S4 object