1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
|
#' @export
standard_error.MCMCglmm <- function(model, ...) {
nF <- model$Fixed$nfl
parms <- as.data.frame(model$Sol[, 1:nF, drop = FALSE])
.data_frame(
Parameter = .remove_backticks_from_string(colnames(parms)),
SE = unname(sapply(parms, stats::sd))
)
}
#' @export
p_value.MCMCglmm <- function(model, ...) {
nF <- model$Fixed$nfl
p <- 1 - colSums(model$Sol[, 1:nF, drop = FALSE] > 0) / dim(model$Sol)[1]
.data_frame(
Parameter = insight::find_parameters(model, effects = "fixed", flatten = TRUE),
p = p
)
}
#' @export
model_parameters.MCMCglmm <- function(model,
centrality = "median",
dispersion = FALSE,
ci = 0.95,
ci_method = "eti",
test = "pd",
rope_range = "default",
rope_ci = 0.95,
bf_prior = NULL,
diagnostic = c("ESS", "Rhat"),
priors = TRUE,
keep = NULL,
drop = NULL,
verbose = TRUE,
...) {
# Processing
params <-
.extract_parameters_bayesian(
model,
centrality = centrality,
dispersion = dispersion,
ci = ci,
ci_method = ci_method,
test = test,
rope_range = rope_range,
rope_ci = rope_ci,
bf_prior = bf_prior,
diagnostic = diagnostic,
priors = priors,
keep_parameters = keep,
drop_parameters = drop,
verbose = verbose,
...
)
attr(params, "pretty_names") <- format_parameters(model)
attr(params, "ci") <- ci
attr(params, "object_name") <- insight::safe_deparse_symbol(substitute(model))
class(params) <- c("parameters_model", "see_parameters_model", class(params))
params
}
|
