dosresmeta (version 1.3.0)

print.dosresmeta: summarizing dosresmeta Models

Description

Print and summary method functions for dose-response models represented in objects of class "dosresmeta".

Usage

## S3 method for class 'dosresmeta':
print(x, digits = 4, ...)

## S3 method for class 'dosresmeta':
summary(object, ci.level = 0.95, ...)

## S3 method for class 'summary.dosresmeta':
print(x, digits = 4, ...)

Arguments

object

an object of class dosresmeta produced by dosresmeta.

x

an object of class dosresmeta or summary.dosresmeta produced by dosresmeta or summary.dosresmeta, respectively.

ci.level

the confidence level used for defining the confidence intervals for the estimates of the (fixed-effects) coefficients.

digits

an integer specifying the number of digits to which printed results must be rounded.

...

further arguments passed to or from other methods.

Value

• The summary method function for dosresmeta objects produces a list of class "summary.dosresmeta" which resembles a list object of class summary.mvmeta. As usual, the print method functions for classes "dosresmeta" and "summary.dosresmeta" do not return any value.

Details

the print method for class dosresmeta only returns basic information of the fitted model, namely the call, estimated (fixed-effects) coefficients, and dimensions. If multiple studies are included in the meta-analysis, it returns also the usual fit statistics (log-likelihood, AIC, BIC). The summary method function computes additional statistics and tests, and produces a list object of class summary.dosresmeta. The print method function for this class, depending on the number of studies included in the analysis, shows additional information, such as tables reporting the estimates for the fixed and random-effects parts of the model, Chi-square test for model significance, Cochran Q test for heterogeneity and I-square.

See Also

dosresmeta, summary

Examples

## Load data and run the model
data("alcohol_cvd")
model <- dosresmeta(formula = logrr ~ dose + I(dose^2), type = type, id = id,
                   se = se, cases = cases, n = n, data = alcohol_cvd)
## Defult print
model
## Specify digits
print(model, digit = 2)
## summary with 90th confidence intervals
summary(model, ci.level = .8)