Learn R Programming

dosresmeta (version 1.3.2)

print.dosresmeta: summarizing dosresmeta Models

Description

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

Usage

"print"(x, digits = 4, ...)
"summary"(object, ci.level = 0.95, ...)
"print"(x, digits = 4, ...)

Arguments

x
an object of class dosresmeta or summary.dosresmeta produced by dosresmeta or summary.dosresmeta, respectively.
digits
an integer specifying the number of digits to which printed results must be rounded.
object
an object of class dosresmeta produced by dosresmeta.
ci.level
the confidence level used for defining the confidence intervals for the estimates of the (fixed-effects) coefficients.
...
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).

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

Run this code
## 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)

Run the code above in your browser using DataLab