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metamisc (version 0.2.4)

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

620

Version

0.2.4

License

GPL-3

Maintainer

Thomas Debray

Last Published

September 2nd, 2021

Functions in metamisc (0.2.4)

Kertai

Kertai data
Framingham

Predictive performance of the Framingham Risk Score in male populations
EuroSCORE

Predictive performance of EuroSCORE II
Fibrinogen

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

Hypothetical dataset for diagnosis of Deep Vein Thrombosis (DVT)
dplot

Posterior distribution of estimated model parameters
Collins

Collins data
dplot.mcmc.list

Posterior distribution of estimated model parameters
Scheidler

Diagnostic accuracy data
Zhang

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

Roberts data
cor2cov

Convert a correlation matrix into a covariance matrix
forest.metapred

Forest plot of a metapred fit
acplot.valmeta

Plot the autocorrelation of a Bayesian meta-analysis model
forest.mp.cv.val

Forest plot of a validation object.
ccalc

Calculate the concordance statistic
fitted.metapred

Extract Model Fitted Values
fat

Regression tests for detecting funnel plot asymmetry
gen

Generalizability estimates
dplot.uvmeta

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

Random effects meta-analysis
metapred

Generalized Stepwise Regression for Prediction Models in Clustered Data
DVTmodels

Risk prediction models for diagnosing Deep Venous Thrombosis (DVT)
Daniels

Daniels and Hughes data
impact

IMPACT data
forest

Forest plot
oecalc

Calculate the total O:E ratio
dplot.valmeta

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

Impute missing values by their conditional mean
plot.uvmeta

Forest Plots
inv.logit

Apply the inverse logit tranformation
rmplot.valmeta

Plot the running means of a Bayesian meta-analysis model
plot.valmeta

Forest Plots
se

Standard errors and variances
logLik.riley

Print the log-likelihood
vcov.riley

Calculate Variance-Covariance Matrix for a Fitted Riley Model Object
riley

Fit the alternative model for bivariate random-effects meta-analysis
predict.riley

Prediction Interval
recalibrate

Recalibrate a Prediction Model
stackedglm

Stacked Regression
forest.default

Forest plot
logit

Apply logit tranformation
metamisc-package

Meta-Analysis of Diagnosis and Prognosis Research Studies
uvmeta

Univariate meta-analysis
valmeta

Meta-analysis of prediction model performance
uvmeta-class

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

Forest Plots
plot.riley

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

Subsetting metapred fits
summary.riley

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.
plot.fat

Display results from the funnel plot asymmetry test
perf

Performance estimates
summary.uvmeta

Summarizing Univariate Meta-Analysis Models