These functions extract or calculate model fit statistics of a
bg_GLM object. These can be found in the output from
summary.lm.
# S3 method for bg_GLM
coef(object, ...)# S3 method for bg_GLM
confint(object, parm, level = 0.95, ...)
# S3 method for bg_GLM
fitted(object, ...)
# S3 method for bg_GLM
residuals(object, type = c("response", "partial"), ...)
# S3 method for bg_GLM
deviance(object, ...)
coeff_determ(object, adjusted = FALSE)
# S3 method for bg_GLM
df.residual(object, ...)
# S3 method for bg_GLM
sigma(object, ...)
# S3 method for bg_GLM
vcov(object, ...)
coeff_table(object, CI = FALSE, level = 0.95)
# S3 method for bg_GLM
anova(object, region = NULL, ...)
A named numeric vector, matrix, or array, depending on the function:
Matrix in which rownames are parameter names and column names are regions
Matrix in which rownames are Study ID's and column
names are regions. If type='partial', an array is returned in
which columns are terms and the 3rd dimension are regions
Numeric vector with elements for each region
Single integer; the degrees of freedom
Numeric array; the extent of the third dimension equals the number of regions
anova returns a list of tables of class anova
A bg_GLM object
Unused
Vector of parameters to calculate confidence intervals for. Default is to use all parameters
The confidence level. Default: 0.95
Character string specifying the type of residuals to return.
Default: 'response'
Logical indicating whether to calculate the adjusted
R-squared. Default: FALSE
Logical indicating whether to include confidence intervals of
parameter estimates in the coefficient summary table. Default: FALSE
Character vector indicating the region(s) to calculate ANOVA
statistics for. Default: NULL (use all regions)
The anova method calculates the so-called Type III test
statistics for a bg_GLM object. These standard ANOVA statistics
include: sum of squares, mean squares, degrees of freedom, F statistics, and
P-values. Additional statistics calculated are: \(\eta^2\), partial
\(\eta^2\), \(\omega^2\), and partial \(\omega^2\) as measures of
effect size.
Christopher G. Watson, cgwatson@bu.edu
These mimic the same functions that operate on lm objects, and
include:
Regression coefficients (parameter estimates)
Confidence intervals (by default, 95%) for parameter estimates
Fitted (mean) values; i.e., the design matrix multiplied by the parameter estimates, \(X \hat{\beta}\)
Model residuals; i.e., the response/outcome variable minus the fitted values. Partial residuals can also be calculated
Model deviance, or the residual sum of squares
Calculate the coefficient of determination (or \(R^2\)), adjusted or unadjusted
Residual degrees of freedom
Residual standard deviation, sometimes called the root mean squared error (RMSE)
Variance-covariance matrix of the model parameters
coeff_table returns model coefficients, standard errors, T-statistics,
and P-values for all model terms and regions in a bg_GLM object. This
is the same as running summary(x)$coefficients for a lm object.
GLM, Anova