Tidy and glance methods for regression tables

tidy() returns one row per parameter, with the model name in a group column, so modelsummary::modelsummary(fit, shape = term ~ group) puts each model in its own column. Standard errors come from the joint covariance matrix. glance() returns the number of observations in the combined sample.

Usage

# S3 method for class 'suest_model'
tidy(x, conf.int = TRUE, conf.level = 0.95, ...)

# S3 method for class 'suest_mi'
tidy(x, conf.int = TRUE, conf.level = 0.95, ...)

# S3 method for class 'suest_model'
glance(x, ...)

# S3 method for class 'suest_mi'
glance(x, ...)

Arguments

x

A "suest_model" or "suest_mi" object.

conf.int

Include confidence intervals.

conf.level

Confidence level.

…

Not used.

Value

A data frame.

Examples

dat <- mtcars
model1 <- glm(am ~ wt, family = binomial(), data = dat)
model2 <- glm(vs ~ wt, family = binomial(), data = dat)
fit <- suest(model1, model2)
if (requireNamespace("generics", quietly = TRUE)) generics::tidy(fit)
         term  group  estimate std.error statistic     p.value  conf.low
1 (Intercept) model1 12.040370 5.0352099  2.391235 0.016791806  2.171540
2          wt model1 -4.023970 1.5826157 -2.542607 0.011002885 -7.125840
3 (Intercept) model2  5.714682 2.0159983  2.834666 0.004587364  1.763397
4          wt model2 -1.910548 0.6093721 -3.135273 0.001716945 -3.104895
   conf.high
1 21.9091998
2 -0.9221002
3  9.6659656
4 -0.7162003
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