Summary method for projoint_results
Source: R/summary.projoint_results.R
summary.projoint_results.Rd
Creates a concise tabular summary of a projoint_results
object,
including the chosen estimand, analysis structure, standard-error settings,
and a data frame of estimates.
Usage
# S3 method for class 'projoint_results'
summary(object, ...)
Value
A data frame (often a tibble) summarizing the estimated effects.
At minimum, it contains the columns produced in object$estimates
(e.g., attribute/level identifiers and the point estimate with its
standard error and confidence interval in columns such as
estimate
, std.error
, conf.low
, conf.high
).
This table is suitable for further processing or printing.
Examples
# \donttest{
data(exampleData1)
# Reshape data for two base tasks + repeated (for IRR estimation)
dat <- reshape_projoint(
exampleData1,
.outcomes = c("choice1", "choice2", "choice1_repeated_flipped")
)
# Build a valid choice-level QoI
att <- unique(dat$labels$attribute_id)[1]
lev_ids <- dat$labels$level_id[dat$labels$attribute_id == att]
lev_names <- sub(".*:", "", lev_ids)
q <- set_qoi(
.structure = "choice_level",
.estimand = "mm",
.att_choose = att,
.lev_choose = lev_names[2],
.att_notchoose = att,
.lev_notchoose = lev_names[1]
)
# Fit model
fit <- projoint(dat, .qoi = q)
# Get the tabular summary of estimates
tab <- summary(fit)
#>
#> Summary of Projoint Estimates
#> ------------------------------
#> Estimand: mm
#> Structure: choice_level
#> Standard error method: analytical
#> SE type (lm_robust): CR2 (clustered by id)
#> IRR: Estimated
#> Tau: 0.172
#>
head(tab)
#> # A tibble: 2 × 7
#> estimand estimate se conf.low conf.high att_level_choose
#> <chr> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 mm_uncorrected 0.406 0.0361 0.334 0.477 att1:level2
#> 2 mm_corrected 0.356 0.0551 0.247 0.465 att1:level2
#> # ℹ 1 more variable: att_level_notchoose <chr>
# }