Summary method for projoint_results
Source: R/summary.projoint_results.R
summary.projoint_results.RdCreates 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>
# }