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metamisc (version 0.2.5)

Meta-Analysis of Diagnosis and Prognosis Research Studies

Description

Facilitate frequentist and Bayesian meta-analysis of diagnosis and prognosis research studies. It includes functions to summarize multiple estimates of prediction model discrimination and calibration performance (Debray et al., 2019) . It also includes functions to evaluate funnel plot asymmetry (Debray et al., 2018) . Finally, the package provides functions for developing multivariable prediction models from datasets with clustering (de Jong et al., 2021) .

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Version

Install

install.packages('metamisc')

Monthly Downloads

800

Version

0.2.5

License

GPL-3

Maintainer

Thomas Debray

Last Published

September 20th, 2021

Functions in metamisc (0.2.5)

Diagnostic accuracy data

Risk prediction models for diagnosing Deep Venous Thrombosis (DVT)

Predictive performance of the Framingham Risk Score in male populations

Daniels and Hughes data

Predictive performance of EuroSCORE II

Meta-analysis of the prognostic role of hormone receptors in endometrial cancer

Hypothetical dataset for diagnosis of Deep Vein Thrombosis (DVT)

Convert a correlation matrix into a covariance matrix

Meta-analysis of the association between plasma fibrinogen concentration and the risk of coronary heath disease

fitted.metapred

Extract Model Fitted Values

Posterior distribution of estimated model parameters

gelmanplot.mcmc.list

Gelman-Rubin-Brooks plot

Plot the prior and posterior distribution of a meta-analysis model

gelmanplot.uvmeta

Gelman-Rubin-Brooks plot

dplot.mcmc.list

Posterior distribution of estimated model parameters

Regression tests for detecting funnel plot asymmetry

Plot the prior and posterior distribution of a meta-analysis model

Plot the autocorrelation of a Bayesian meta-analysis model

forest.mp.cv.val

Forest plot of a validation object.

Calculate the concordance statistic

forest.metapred

Forest plot of a metapred fit

gelmanplot.valmeta

Gelman-Rubin-Brooks plot

Plot the autocorrelation of a Bayesian meta-analysis model

acplot.mcmc.list

Plot the autocorrelation of a Bayesian meta-analysis model

Apply logit tranformation

Plot the autocorrelation of a Bayesian meta-analysis model

Display results from the funnel plot asymmetry test

Random effects meta-analysis

Gelman-Rubin-Brooks plot

Recalibrate a Prediction Model

Summarizing Univariate Meta-Analysis Models

Generalizability estimates

Class "uvmeta". Result of a univariate meta-analysis.

Fit the alternative model for bivariate random-effects meta-analysis

Apply the inverse logit tranformation

Plot the summary of the bivariate model from Riley et al. (2008).

impute_conditional_mean

Impute missing values by their conditional mean

Plot the running means of a Bayesian meta-analysis model

rmplot.mcmc.list

Plot the running means of a Bayesian meta-analysis model

Calculate the total O:E ratio

Print the log-likelihood

Performance estimates

metamisc-package

Meta-Analysis of Diagnosis and Prognosis Research Studies

Parameter summaries Provides the summary estimates of the alternative model for bivariate random-effects meta-analysis by Riley et al. (2008) with their corresponding standard errors (derived from the inverse Hessian). For confidence intervals, asymptotic normality is assumed.

Univariate meta-analysis

subset.metapred

Subsetting metapred fits

Calculate Variance-Covariance Matrix for a Fitted Riley Model Object

Stacked Regression

Standard errors and variances

Meta-analysis of prediction model performance

Plot the running means of a Bayesian meta-analysis model

Prediction Interval

Generalized Stepwise Regression for Prediction Models in Clustered Data

Plot the running means of a Bayesian meta-analysis model