R: Meta-Analysis of Diagnosis and Prognosis Research Studies

# Meta-Analysis of Diagnosis and Prognosis Research Studies

## Documentation for package ‘metamisc’ version 0.4.0

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

metamisc-package | Meta-Analysis of Diagnosis and Prognosis Research Studies
acplot | Plot the autocorrelation of a Bayesian meta-analysis model
acplot.mcmc.list | Plot the autocorrelation of a Bayesian meta-analysis model
acplot.uvmeta | Plot the autocorrelation of a Bayesian meta-analysis model
acplot.valmeta | Plot the autocorrelation of a Bayesian meta-analysis model
ccalc | Calculate the concordance statistic
Collins | Collins data
cor2cov | Convert a correlation matrix into a covariance matrix
Daniels | Daniels and Hughes data
dplot | Posterior distribution of estimated model parameters
dplot.mcmc.list | Posterior distribution of estimated model parameters
dplot.uvmeta | Plot the prior and posterior distribution of a meta-analysis model
dplot.valmeta | Plot the prior and posterior distribution of a meta-analysis model
DVTipd | Hypothetical dataset for diagnosis of Deep Vein Thrombosis (DVT)
DVTmodels | Risk prediction models for diagnosing Deep Venous Thrombosis (DVT)
EuroSCORE | Predictive performance of EuroSCORE II
fat | Regression tests for detecting funnel plot asymmetry
Fibrinogen | Meta-analysis of the association between plasma fibrinogen concentration and the risk of coronary heath disease
fitted.metapred | Extract Model Fitted Values
forest | Forest plot
forest.default | Forest plot
forest.metapred | Forest plot of a metapred fit
forest.mp.cv.val | Forest plot of a validation object.
forest.perf | Forest plot of a validation object.
Framingham | Predictive performance of the Framingham Risk Score in male populations
gelmanplot | Gelman-Rubin-Brooks plot
gelmanplot.mcmc.list | Gelman-Rubin-Brooks plot
gelmanplot.uvmeta | Gelman-Rubin-Brooks plot
gelmanplot.valmeta | Gelman-Rubin-Brooks plot
gen | Generalizability estimates
generalizability | Generalizability estimates
impact | IMPACT data
impute_conditional_mean | Impute missing values by their conditional mean
inv.logit | Apply the inverse logit tranformation
Kertai | Kertai data
logit | Apply logit tranformation
logLik.riley | Print the log-likelihood
ma | Random effects meta-analysis
metapred | Generalized Stepwise Regression for Prediction Models in Clustered Data
oecalc | Calculate the total O:E ratio
perf | Performance estimates
performance | Performance estimates
plot.fat | Display results from the funnel plot asymmetry test
plot.mm_perf | Forest Plots
plot.riley | Plot the summary of the bivariate model from Riley et al. (2008).
plot.uvmeta | Forest Plots
plot.valmeta | Forest Plots
predict.riley | Prediction Interval
recalibrate | Recalibrate a Prediction Model
riley | Fit the alternative model for bivariate random-effects meta-analysis
rmplot | Plot the running means of a Bayesian meta-analysis model
rmplot.mcmc.list | Plot the running means of a Bayesian meta-analysis model
rmplot.uvmeta | Plot the running means of a Bayesian meta-analysis model
rmplot.valmeta | Plot the running means of a Bayesian meta-analysis model
Roberts | Roberts data
Scheidler | Diagnostic accuracy data
se | Standard errors and variances
stackedglm | Stacked Regression
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.
summary.uvmeta | Summarizing Univariate Meta-Analysis Models
tau | Standard errors and variances
tau2 | Standard errors and variances
uvmeta | Univariate meta-analysis
uvmeta-clas | Class "uvmeta". Result of a univariate meta-analysis.
valmeta | Meta-analysis of prediction model performance
variances | Standard errors and variances
vcov.riley | Calculate Variance-Covariance Matrix for a Fitted Riley Model Object
Zhang | Meta-analysis of the prognostic role of hormone receptors in endometrial cancer