R/gamljglm.h.R
In mcfanda/gamlj: GAMLj Suite for linear models
# This file is automatically generated, you probably don't want to edit this
gamljglmOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"gamljglmOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
.caller = "glm",
.interface = "jamovi",
dep = NULL,
dep2 = NULL,
factors = NULL,
covs = NULL,
offset = NULL,
model_terms = NULL,
fixed_intercept = TRUE,
nested_intercept = TRUE,
nested_terms = NULL,
comparison = FALSE,
estimates_ci = FALSE,
donotrun = FALSE,
input_method = "standard",
ci_method = "wald",
boot_r = 1000,
ci_width = 95,
contrasts = NULL,
show_contrastnames = FALSE,
show_contrastcodes = FALSE,
vcov = FALSE,
crosstab = FALSE,
plot_x = NULL,
plot_z = NULL,
plot_by = NULL,
plot_raw = FALSE,
plot_yscale = FALSE,
plot_xoriginal = FALSE,
plot_black = FALSE,
plot_around = "ci",
emmeans = NULL,
posthoc = NULL,
posthoc_ci = FALSE,
simple_x = NULL,
simple_mods = NULL,
simple_interactions = FALSE,
covs_conditioning = "mean_sd",
ccra_steps = 1,
ccm_value = 1,
ccp_value = 25,
covs_scale_labels = "labels",
adjust = list(
"bonf"),
covs_scale = NULL,
scale_missing = "complete",
mute = FALSE,
expb_ci = TRUE,
es = list(
"expb"),
model_type = "linear",
custom_family = "gaussian",
custom_link = "identity",
propodds_test = FALSE,
preds_phi = FALSE,
plot_scale = "response", ...) {
super$initialize(
package="GAMLj3",
name="gamljglm",
requiresData=TRUE,
...)
private$...caller <- jmvcore::OptionString$new(
".caller",
.caller,
default="glm",
hidden=TRUE)
private$...interface <- jmvcore::OptionString$new(
".interface",
.interface,
default="jamovi",
hidden=TRUE)
private$..dep <- jmvcore::OptionVariable$new(
"dep",
dep,
default=NULL,
permitted=list(
"factor",
"numeric"))
private$..dep2 <- jmvcore::OptionVariable$new(
"dep2",
dep2,
default=NULL,
permitted=list(
"factor",
"numeric"))
private$..factors <- jmvcore::OptionVariables$new(
"factors",
factors,
suggested=list(
"nominal"),
permitted=list(
"factor"),
default=NULL)
private$..covs <- jmvcore::OptionVariables$new(
"covs",
covs,
suggested=list(
"continuous",
"ordinal"),
permitted=list(
"numeric"),
default=NULL)
private$..offset <- jmvcore::OptionVariable$new(
"offset",
offset,
default=NULL)
private$..model_terms <- jmvcore::OptionTerms$new(
"model_terms",
model_terms,
default=NULL)
private$..fixed_intercept <- jmvcore::OptionBool$new(
"fixed_intercept",
fixed_intercept,
default=TRUE)
private$..nested_intercept <- jmvcore::OptionBool$new(
"nested_intercept",
nested_intercept,
default=TRUE)
private$..nested_terms <- jmvcore::OptionTerms$new(
"nested_terms",
nested_terms,
default=NULL)
private$..comparison <- jmvcore::OptionBool$new(
"comparison",
comparison,
default=FALSE)
private$..estimates_ci <- jmvcore::OptionBool$new(
"estimates_ci",
estimates_ci,
default=FALSE)
private$..donotrun <- jmvcore::OptionBool$new(
"donotrun",
donotrun,
default=FALSE)
private$..input_method <- jmvcore::OptionList$new(
"input_method",
input_method,
default="standard",
options=list(
"standard",
"success",
"total"))
private$..ci_method <- jmvcore::OptionList$new(
"ci_method",
ci_method,
default="wald",
options=list(
"wald",
"profile",
"quantile",
"bcai"))
private$..boot_r <- jmvcore::OptionNumber$new(
"boot_r",
boot_r,
min=1,
default=1000)
private$..ci_width <- jmvcore::OptionNumber$new(
"ci_width",
ci_width,
min=50,
max=99.9,
default=95)
private$..contrasts <- jmvcore::OptionArray$new(
"contrasts",
contrasts,
items="(factors)",
default=NULL,
template=jmvcore::OptionGroup$new(
"contrasts",
NULL,
elements=list(
jmvcore::OptionVariable$new(
"var",
NULL,
content="$key"),
jmvcore::OptionList$new(
"type",
NULL,
options=list(
"simple",
"deviation",
"dummy",
"difference",
"helmert",
"repeated",
"polynomial"),
default="simple"))))
private$..show_contrastnames <- jmvcore::OptionBool$new(
"show_contrastnames",
show_contrastnames,
default=FALSE)
private$..show_contrastcodes <- jmvcore::OptionBool$new(
"show_contrastcodes",
show_contrastcodes,
default=FALSE)
private$..vcov <- jmvcore::OptionBool$new(
"vcov",
vcov,
default=FALSE)
private$..crosstab <- jmvcore::OptionBool$new(
"crosstab",
crosstab,
default=FALSE)
private$..plot_x <- jmvcore::OptionVariable$new(
"plot_x",
plot_x,
default=NULL)
private$..plot_z <- jmvcore::OptionVariable$new(
"plot_z",
plot_z,
default=NULL)
private$..plot_by <- jmvcore::OptionVariables$new(
"plot_by",
plot_by,
default=NULL)
private$..plot_raw <- jmvcore::OptionBool$new(
"plot_raw",
plot_raw,
default=FALSE)
private$..plot_yscale <- jmvcore::OptionBool$new(
"plot_yscale",
plot_yscale,
default=FALSE)
private$..plot_xoriginal <- jmvcore::OptionBool$new(
"plot_xoriginal",
plot_xoriginal,
default=FALSE)
private$..plot_black <- jmvcore::OptionBool$new(
"plot_black",
plot_black,
default=FALSE)
private$..plot_around <- jmvcore::OptionList$new(
"plot_around",
plot_around,
options=list(
"none",
"ci",
"se"),
default="ci")
private$..emmeans <- jmvcore::OptionTerms$new(
"emmeans",
emmeans,
default=NULL)
private$..posthoc <- jmvcore::OptionTerms$new(
"posthoc",
posthoc,
default=NULL)
private$..posthoc_ci <- jmvcore::OptionBool$new(
"posthoc_ci",
posthoc_ci,
default=FALSE)
private$..simple_x <- jmvcore::OptionVariable$new(
"simple_x",
simple_x,
default=NULL)
private$..simple_mods <- jmvcore::OptionVariables$new(
"simple_mods",
simple_mods,
default=NULL)
private$..simple_interactions <- jmvcore::OptionBool$new(
"simple_interactions",
simple_interactions,
default=FALSE)
private$..covs_conditioning <- jmvcore::OptionList$new(
"covs_conditioning",
covs_conditioning,
options=list(
"mean_sd",
"percent",
"range"),
default="mean_sd")
private$..ccra_steps <- jmvcore::OptionNumber$new(
"ccra_steps",
ccra_steps,
default=1,
min=1,
max=50)
private$..ccm_value <- jmvcore::OptionNumber$new(
"ccm_value",
ccm_value,
default=1)
private$..ccp_value <- jmvcore::OptionNumber$new(
"ccp_value",
ccp_value,
default=25,
min=5,
max=50)
private$..covs_scale_labels <- jmvcore::OptionList$new(
"covs_scale_labels",
covs_scale_labels,
options=list(
"labels",
"values",
"values_labels",
"uvalues",
"uvalues_labels"),
default="labels")
private$..adjust <- jmvcore::OptionNMXList$new(
"adjust",
adjust,
options=list(
"none",
"bonf",
"tukey",
"holm",
"scheffe",
"sidak"),
default=list(
"bonf"))
private$..predicted <- jmvcore::OptionOutput$new(
"predicted")
private$..residuals <- jmvcore::OptionOutput$new(
"residuals")
private$..covs_scale <- jmvcore::OptionArray$new(
"covs_scale",
covs_scale,
items="(covs)",
default=NULL,
template=jmvcore::OptionGroup$new(
"covs_scale",
NULL,
elements=list(
jmvcore::OptionVariable$new(
"var",
NULL,
content="$key"),
jmvcore::OptionList$new(
"type",
NULL,
options=list(
"centered",
"standardized",
"none"),
default="centered"))))
private$..scale_missing <- jmvcore::OptionList$new(
"scale_missing",
scale_missing,
options=list(
"complete",
"colwise"),
default="complete")
private$..mute <- jmvcore::OptionBool$new(
"mute",
mute,
default=FALSE)
private$..expb_ci <- jmvcore::OptionBool$new(
"expb_ci",
expb_ci,
default=TRUE)
private$..es <- jmvcore::OptionNMXList$new(
"es",
es,
options=list(
"expb",
"RR",
"marginals"),
default=list(
"expb"))
private$..model_type <- jmvcore::OptionList$new(
"model_type",
model_type,
options=list(
"linear",
"poisson",
"poiover",
"nb",
"logistic",
"probit",
"probit",
"beta",
"ordinal",
"multinomial",
"custom"),
default="linear")
private$..custom_family <- jmvcore::OptionList$new(
"custom_family",
custom_family,
options=list(
"gaussian",
"binomial",
"poisson",
"inverse.gaussian",
"Gamma"),
default="gaussian")
private$..custom_link <- jmvcore::OptionList$new(
"custom_link",
custom_link,
options=list(
"identity",
"logit",
"log",
"inverse",
"1/mu^2",
"sqrt"),
default="identity")
private$..propodds_test <- jmvcore::OptionBool$new(
"propodds_test",
propodds_test,
default=FALSE)
private$..preds_phi <- jmvcore::OptionBool$new(
"preds_phi",
preds_phi,
default=FALSE)
private$..plot_scale <- jmvcore::OptionList$new(
"plot_scale",
plot_scale,
options=list(
"response",
"link",
"mean.class"),
default="response")
self$.addOption(private$...caller)
self$.addOption(private$...interface)
self$.addOption(private$..dep)
self$.addOption(private$..dep2)
self$.addOption(private$..factors)
self$.addOption(private$..covs)
self$.addOption(private$..offset)
self$.addOption(private$..model_terms)
self$.addOption(private$..fixed_intercept)
self$.addOption(private$..nested_intercept)
self$.addOption(private$..nested_terms)
self$.addOption(private$..comparison)
self$.addOption(private$..estimates_ci)
self$.addOption(private$..donotrun)
self$.addOption(private$..input_method)
self$.addOption(private$..ci_method)
self$.addOption(private$..boot_r)
self$.addOption(private$..ci_width)
self$.addOption(private$..contrasts)
self$.addOption(private$..show_contrastnames)
self$.addOption(private$..show_contrastcodes)
self$.addOption(private$..vcov)
self$.addOption(private$..crosstab)
self$.addOption(private$..plot_x)
self$.addOption(private$..plot_z)
self$.addOption(private$..plot_by)
self$.addOption(private$..plot_raw)
self$.addOption(private$..plot_yscale)
self$.addOption(private$..plot_xoriginal)
self$.addOption(private$..plot_black)
self$.addOption(private$..plot_around)
self$.addOption(private$..emmeans)
self$.addOption(private$..posthoc)
self$.addOption(private$..posthoc_ci)
self$.addOption(private$..simple_x)
self$.addOption(private$..simple_mods)
self$.addOption(private$..simple_interactions)
self$.addOption(private$..covs_conditioning)
self$.addOption(private$..ccra_steps)
self$.addOption(private$..ccm_value)
self$.addOption(private$..ccp_value)
self$.addOption(private$..covs_scale_labels)
self$.addOption(private$..adjust)
self$.addOption(private$..predicted)
self$.addOption(private$..residuals)
self$.addOption(private$..covs_scale)
self$.addOption(private$..scale_missing)
self$.addOption(private$..mute)
self$.addOption(private$..expb_ci)
self$.addOption(private$..es)
self$.addOption(private$..model_type)
self$.addOption(private$..custom_family)
self$.addOption(private$..custom_link)
self$.addOption(private$..propodds_test)
self$.addOption(private$..preds_phi)
self$.addOption(private$..plot_scale)
}),
active = list(
.caller = function() private$...caller$value,
.interface = function() private$...interface$value,
dep = function() private$..dep$value,
dep2 = function() private$..dep2$value,
factors = function() private$..factors$value,
covs = function() private$..covs$value,
offset = function() private$..offset$value,
model_terms = function() private$..model_terms$value,
fixed_intercept = function() private$..fixed_intercept$value,
nested_intercept = function() private$..nested_intercept$value,
nested_terms = function() private$..nested_terms$value,
comparison = function() private$..comparison$value,
estimates_ci = function() private$..estimates_ci$value,
donotrun = function() private$..donotrun$value,
input_method = function() private$..input_method$value,
ci_method = function() private$..ci_method$value,
boot_r = function() private$..boot_r$value,
ci_width = function() private$..ci_width$value,
contrasts = function() private$..contrasts$value,
show_contrastnames = function() private$..show_contrastnames$value,
show_contrastcodes = function() private$..show_contrastcodes$value,
vcov = function() private$..vcov$value,
crosstab = function() private$..crosstab$value,
plot_x = function() private$..plot_x$value,
plot_z = function() private$..plot_z$value,
plot_by = function() private$..plot_by$value,
plot_raw = function() private$..plot_raw$value,
plot_yscale = function() private$..plot_yscale$value,
plot_xoriginal = function() private$..plot_xoriginal$value,
plot_black = function() private$..plot_black$value,
plot_around = function() private$..plot_around$value,
emmeans = function() private$..emmeans$value,
posthoc = function() private$..posthoc$value,
posthoc_ci = function() private$..posthoc_ci$value,
simple_x = function() private$..simple_x$value,
simple_mods = function() private$..simple_mods$value,
simple_interactions = function() private$..simple_interactions$value,
covs_conditioning = function() private$..covs_conditioning$value,
ccra_steps = function() private$..ccra_steps$value,
ccm_value = function() private$..ccm_value$value,
ccp_value = function() private$..ccp_value$value,
covs_scale_labels = function() private$..covs_scale_labels$value,
adjust = function() private$..adjust$value,
predicted = function() private$..predicted$value,
residuals = function() private$..residuals$value,
covs_scale = function() private$..covs_scale$value,
scale_missing = function() private$..scale_missing$value,
mute = function() private$..mute$value,
expb_ci = function() private$..expb_ci$value,
es = function() private$..es$value,
model_type = function() private$..model_type$value,
custom_family = function() private$..custom_family$value,
custom_link = function() private$..custom_link$value,
propodds_test = function() private$..propodds_test$value,
preds_phi = function() private$..preds_phi$value,
plot_scale = function() private$..plot_scale$value),
private = list(
...caller = NA,
...interface = NA,
..dep = NA,
..dep2 = NA,
..factors = NA,
..covs = NA,
..offset = NA,
..model_terms = NA,
..fixed_intercept = NA,
..nested_intercept = NA,
..nested_terms = NA,
..comparison = NA,
..estimates_ci = NA,
..donotrun = NA,
..input_method = NA,
..ci_method = NA,
..boot_r = NA,
..ci_width = NA,
..contrasts = NA,
..show_contrastnames = NA,
..show_contrastcodes = NA,
..vcov = NA,
..crosstab = NA,
..plot_x = NA,
..plot_z = NA,
..plot_by = NA,
..plot_raw = NA,
..plot_yscale = NA,
..plot_xoriginal = NA,
..plot_black = NA,
..plot_around = NA,
..emmeans = NA,
..posthoc = NA,
..posthoc_ci = NA,
..simple_x = NA,
..simple_mods = NA,
..simple_interactions = NA,
..covs_conditioning = NA,
..ccra_steps = NA,
..ccm_value = NA,
..ccp_value = NA,
..covs_scale_labels = NA,
..adjust = NA,
..predicted = NA,
..residuals = NA,
..covs_scale = NA,
..scale_missing = NA,
..mute = NA,
..expb_ci = NA,
..es = NA,
..model_type = NA,
..custom_family = NA,
..custom_link = NA,
..propodds_test = NA,
..preds_phi = NA,
..plot_scale = NA)
)
gamljglmResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"gamljglmResults",
inherit = jmvcore::Group,
active = list(
model = function() private$..model,
info = function() private$.items[["info"]],
main = function() private$.items[["main"]],
posthoc = function() private$.items[["posthoc"]],
simpleEffects = function() private$.items[["simpleEffects"]],
simpleInteractions = function() private$.items[["simpleInteractions"]],
emmeans = function() private$.items[["emmeans"]],
mainPlots = function() private$.items[["mainPlots"]],
plotnotes = function() private$.items[["plotnotes"]],
predicted = function() private$.items[["predicted"]],
residuals = function() private$.items[["residuals"]]),
private = list(
..model = NA),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Generalized Linear Model")
private$..model <- NULL
self$add(jmvcore::Table$new(
options=options,
name="info",
title="Model Info",
columns=list(
list(
`name`="info",
`type`="text",
`title`="Info"),
list(
`name`="value",
`type`="text",
`title`=""),
list(
`name`="specs",
`type`="text",
`title`="")),
refs="gamlj"))
self$add(R6::R6Class(
inherit = jmvcore::Group,
active = list(
r2 = function() private$.items[["r2"]],
fit = function() private$.items[["fit"]],
crosstab = function() private$.items[["crosstab"]],
anova = function() private$.items[["anova"]],
coefficients = function() private$.items[["coefficients"]],
phi = function() private$.items[["phi"]],
vcov = function() private$.items[["vcov"]],
contrastCodeTables = function() private$.items[["contrastCodeTables"]],
marginals = function() private$.items[["marginals"]],
relativerisk = function() private$.items[["relativerisk"]],
paralleltest = function() private$.items[["paralleltest"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="main",
title="Model Results")
self$add(jmvcore::Table$new(
options=options,
name="r2",
title="Model Fit",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"nested_terms",
"nested_intercept",
"comparison"),
rows=1,
columns=list(
list(
`name`="model",
`title`="Model",
`visible`="(comparison)"),
list(
`name`="r2",
`title`="R\u00B2",
`type`="number"),
list(
`name`="ar2",
`title`="Adj. R\u00B2",
`type`="number"),
list(
`name`="df1",
`title`="df",
`type`="integer"),
list(
`name`="test",
`title`="X\u00B2",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue")),
refs="goodness"))
self$add(jmvcore::Table$new(
options=options,
name="fit",
title="Additional indices",
visible=TRUE,
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link"),
columns=list(
list(
`name`="info",
`type`="text",
`title`="Info"),
list(
`name`="value",
`type`="text",
`title`="Model Value"),
list(
`name`="nested",
`type`="text",
`title`="Nested Model",
`visible`="(comparison)"),
list(
`name`="diff",
`type`="text",
`title`="\u0394",
`visible`="(comparison)"),
list(
`name`="specs",
`type`="text",
`title`="Comment"))))
self$add(jmvcore::Table$new(
options=options,
name="crosstab",
title="Classification table",
visible="(crosstab)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link"),
columns=list(
list(
`name`="obs",
`title`="Observed",
`type`="integer"))))
self$add(jmvcore::Table$new(
options=options,
name="anova",
title="Omnibus tests",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link"),
columns=list(
list(
`name`="source",
`title`="",
`type`="text"),
list(
`name`="test",
`title`="X\u00B2",
`type`="number"),
list(
`name`="df",
`title`="df",
`type`="integer"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="coefficients",
title="Parameter Estimates (Coefficients)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"ci_width",
"ci_method",
"boot_r"),
columns=list(
list(
`name`="response",
`title`="Response",
`type`="text",
`visible`="(model_type:multinomial)",
`combineBelow`=TRUE),
list(
`name`="source",
`title`="Name",
`type`="text"),
list(
`name`="label",
`title`="Effect",
`type`="text",
`visible`="(show_contrastnames)"),
list(
`name`="estimate",
`title`="Estimate",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(estimates_ci)"),
list(
`name`="est.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(estimates_ci)"),
list(
`name`="expb",
`type`="number",
`title`="Exp(B)",
`visible`="(es:expb)"),
list(
`name`="expb.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(es:expb & expb_ci)"),
list(
`name`="expb.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(es:expb & expb_ci)"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="phi",
title="Precision Parameter Estimates (phi)",
visible="(model_type:beta)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"ci_width",
"ci_method",
"boot_r"),
columns=list(
list(
`name`="source",
`title`="Name",
`type`="text"),
list(
`name`="label",
`title`="Effect",
`type`="text",
`visible`="(show_contrastnames)"),
list(
`name`="estimate",
`title`="Estimate",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`type`="number",
`title`="Lower"),
list(
`name`="est.ci.upper",
`type`="number",
`title`="Upper"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="vcov",
title="Coefficients Covariances",
visible="(vcov)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link"),
columns=list(
list(
`name`="source",
`title`="Coefficient",
`type`="text",
`visible`="(show_contrastnames)"))))
self$add(jmvcore::Array$new(
options=options,
name="contrastCodeTables",
title="Contrast Coefficients",
visible="(show_contrastcodes)",
items="(factors)",
clearWith=list(
"contrasts"),
template=jmvcore::Table$new(
options=options,
title="$key",
columns=list(
list(
`name`="cname",
`title`="Name",
`type`="text",
`visible`="(show_contrastnames)"),
list(
`name`="clab",
`title`="Contrast",
`type`="text"),
list(
`name`="bogus",
`title`="bogus",
`type`="text",
`visible`=FALSE)))))
self$add(jmvcore::Table$new(
options=options,
name="marginals",
title="Marginal Effects",
visible="(es:marginals)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"simple_x",
"simple_mods",
"simple_scale",
"ccm_value",
"ccp_value",
"ccra_steps",
"covs_scale_labels",
"covs_conditioning"),
columns=list(
list(
`name`="response",
`title`="Response",
`type`="text",
`combineBelow`=TRUE,
`visible`="(model_type:multinomial)"),
list(
`name`="source",
`title`="Name",
`type`="text"),
list(
`name`="contrast",
`title`="Effect",
`type`="text"),
list(
`name`="estimate",
`title`="AME",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(expb_ci | estimates_ci)"),
list(
`name`="est.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(expb_ci | estimates_ci)"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="relativerisk",
title="Relative risk",
visible="(es:RR)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"__effectsizeoptions"),
columns=list(
list(
`name`="source",
`title`="Name",
`type`="text",
`visible`="(show_contrastnames)"),
list(
`name`="label",
`title`="Effect",
`type`="text"),
list(
`name`="estimate",
`title`="RR",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(expb_ci | estimates_ci)"),
list(
`name`="est.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(expb_ci | estimates_ci)"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="paralleltest",
title="Parallel lines test",
visible="(propodds_test & model_type:ordinal)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"propodds_test"),
columns=list(
list(
`name`="source",
`title`="",
`type`="text"),
list(
`name`="loglik",
`title`="Log-Lik.",
`type`="number"),
list(
`name`="aic",
`title`="AIC",
`type`="number"),
list(
`name`="test",
`title`="X\u00B2",
`type`="number"),
list(
`name`="df",
`title`="df",
`type`="integer"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))}))$new(options=options))
self$add(jmvcore::Array$new(
options=options,
name="posthoc",
title="Post Hoc Tests",
items="(posthoc)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"posthoc",
"adjust",
"ci_width",
"ci_method",
"boot_r"),
template=jmvcore::Table$new(
options=options,
title="",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"posthoc",
"adjust",
"ci_width",
"ci_method",
"boot_r"),
columns=list(
list(
`name`="response",
`title`="Response",
`type`="text",
`visible`="(model_type:multinomial)",
`combineBelow`=TRUE),
list(
`name`="estimate",
`title`="Difference",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(posthoc_ci)"),
list(
`name`="est.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(posthoc_ci)"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="none",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(adjust:none)"),
list(
`name`="bonf",
`title`="p<sub>bonferroni</sub>",
`type`="number",
`format`="zto,pvalue",
`visible`="(adjust:bonf)"),
list(
`name`="tukey",
`title`="p<sub>tukey</sub>",
`type`="number",
`format`="zto,pvalue",
`visible`="(adjust:tukey)"),
list(
`name`="holm",
`title`="p<sub>holm</sub>",
`type`="number",
`format`="zto,pvalue",
`visible`="(adjust:holm)")))))
self$add(R6::R6Class(
inherit = jmvcore::Group,
active = list(
anova = function() private$.items[["anova"]],
coefficients = function() private$.items[["coefficients"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="simpleEffects",
title="Simple Effects")
self$add(jmvcore::Table$new(
options=options,
name="anova",
title="ANOVA for Simple Effects of ___key___",
visible=FALSE,
clearWith=list(
"dep",
"model_terms",
"contrasts",
"covs_conditioning",
"fixed_intercept",
"simple_effects",
"simple_moderators",
"covs_scale",
"ccm_value",
"ccp_value",
"covs_scale_labels",
"offset"),
columns=list(
list(
`name`="test",
`title`="X\u00B2",
`type`="number"),
list(
`name`="df1",
`title`="df",
`type`="integer"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="coefficients",
title="Parameter Estimates for simple effects of ___key___",
visible=FALSE,
clearWith=list(
"dep",
"model_terms",
"contrasts",
"covs_conditioning",
"dep_scale",
"fixed_intercept",
"simple_effects",
"simple_moderators",
"covs_scale",
"ccm_value",
"ccp_value",
"covs_scale_labels",
"ci_method",
"boot_r",
"offset"),
columns=list(
list(
`name`="response",
`title`="Response",
`type`="text",
`combineBelow`=TRUE,
`visible`="(model_type:multinomial)"),
list(
`name`="contrast",
`title`="Effect",
`type`="text"),
list(
`name`="estimate",
`title`="Estimate",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(estimates_ci)"),
list(
`name`="est.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(estimates_ci)"),
list(
`name`="expb",
`type`="number",
`title`="Exp(B)",
`visible`="(es:expb)"),
list(
`name`="expb.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(expb_ci)"),
list(
`name`="expb.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(expb_ci)"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))}))$new(options=options))
self$add(jmvcore::Array$new(
options=options,
name="simpleInteractions",
title="Simple Interactions",
visible=FALSE,
clearWith=list(
"dep",
"model_terms",
"contrasts",
"covs_conditioning",
"dep_scale",
"fixed_intercept",
"covs_scale_labels",
"ci_width",
"emmeans",
"offset"),
template=R6::R6Class(
inherit = jmvcore::Group,
active = list(
anova = function() private$.items[["anova"]],
coefficients = function() private$.items[["coefficients"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="undefined",
title="Interaction: ___key___",
clearWith=list())
self$add(jmvcore::Table$new(
options=options,
name="anova",
title="ANOVA test - $key",
columns=list(
list(
`name`="effect",
`title`="Effect",
`type`="text"),
list(
`name`="test",
`title`="X\u00B2",
`type`="number"),
list(
`name`="df1",
`title`="df",
`type`="integer"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="coefficients",
title="Parameter Estimates for - $key",
columns=list(
list(
`name`="effect",
`title`="Effect",
`type`="text"),
list(
`name`="response",
`title`="Response",
`type`="text",
`visible`="(model_type:multinomial)"),
list(
`name`="estimate",
`title`="Estimate",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`title`="Lower",
`type`="number"),
list(
`name`="est.ci.upper",
`title`="Upper",
`type`="number"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"),
list(
`name`="expb",
`type`="number",
`title`="Exp(B)",
`visible`="(es:expb)"),
list(
`name`="expb.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(expb_ci)",
`superTitle`="Exp(B) Confidence Intervals"),
list(
`name`="expb.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(expb_ci)",
`superTitle`="Exp(B) Confidence Intervals"))))}))$new(options=options)))
self$add(jmvcore::Array$new(
options=options,
name="emmeans",
title="Estimated Marginal Means",
visible=FALSE,
items="(emmeans)",
template=jmvcore::Table$new(
options=options,
title="Estimate Marginal Means - ___key___",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"ci_width",
"ci_method",
"boot_r"),
columns=list(
list(
`name`="response",
`title`="Response",
`type`="text",
`visible`="(model_type:multinomial)",
`combineBelow`=TRUE),
list(
`name`="estimate",
`title`="Mean",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`title`="Lower",
`type`="number"),
list(
`name`="est.ci.upper",
`title`="Upper",
`type`="number")))))
self$add(jmvcore::Array$new(
options=options,
name="mainPlots",
title="Results Plots",
template=jmvcore::Image$new(
options=options,
title="",
renderFun=".mainPlot",
width=600,
height=400,
clearWith=list(
"dep",
"plot_x",
"plot_z",
"plot_by",
"plot_raw",
"plot_yscale",
"plot_scale",
"plot_xoriginal",
"plot_black",
"plot_around",
"ci_width",
"covs_scale",
"dep_scale",
"model_terms",
"fixed_intercept",
"covs_conditioning",
"covs_scale_labels",
"ccp_value",
"ccm_value"))))
self$add(jmvcore::Html$new(
options=options,
name="plotnotes",
visible=FALSE))
self$add(jmvcore::Output$new(
options=options,
name="predicted",
title="Predicted Vales",
varTitle="`GLM_${ dep }_PRED`",
varDescription="Predicted values",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link")))
self$add(jmvcore::Output$new(
options=options,
name="residuals",
title="Residuals Vales",
varTitle="`GLM_${ dep }_RES`",
varDescription="Residuals values",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link")))},
.setModel=function(x) private$..model <- x))
gamljglmBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"gamljglmBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "GAMLj3",
name = "gamljglm",
version = c(3,0,0),
options = options,
results = gamljglmResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE,
requiresMissings = FALSE,
weightsSupport = 'none')
}))
mcfanda/gamlj documentation built on April 15, 2024, 11:16 a.m.
R Package Documentation
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# This file is automatically generated, you probably don't want to edit this
gamljglmOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"gamljglmOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
.caller = "glm",
.interface = "jamovi",
dep = NULL,
dep2 = NULL,
factors = NULL,
covs = NULL,
offset = NULL,
model_terms = NULL,
fixed_intercept = TRUE,
nested_intercept = TRUE,
nested_terms = NULL,
comparison = FALSE,
estimates_ci = FALSE,
donotrun = FALSE,
input_method = "standard",
ci_method = "wald",
boot_r = 1000,
ci_width = 95,
contrasts = NULL,
show_contrastnames = FALSE,
show_contrastcodes = FALSE,
vcov = FALSE,
crosstab = FALSE,
plot_x = NULL,
plot_z = NULL,
plot_by = NULL,
plot_raw = FALSE,
plot_yscale = FALSE,
plot_xoriginal = FALSE,
plot_black = FALSE,
plot_around = "ci",
emmeans = NULL,
posthoc = NULL,
posthoc_ci = FALSE,
simple_x = NULL,
simple_mods = NULL,
simple_interactions = FALSE,
covs_conditioning = "mean_sd",
ccra_steps = 1,
ccm_value = 1,
ccp_value = 25,
covs_scale_labels = "labels",
adjust = list(
"bonf"),
covs_scale = NULL,
scale_missing = "complete",
mute = FALSE,
expb_ci = TRUE,
es = list(
"expb"),
model_type = "linear",
custom_family = "gaussian",
custom_link = "identity",
propodds_test = FALSE,
preds_phi = FALSE,
plot_scale = "response", ...) {
super$initialize(
package="GAMLj3",
name="gamljglm",
requiresData=TRUE,
...)
private$...caller <- jmvcore::OptionString$new(
".caller",
.caller,
default="glm",
hidden=TRUE)
private$...interface <- jmvcore::OptionString$new(
".interface",
.interface,
default="jamovi",
hidden=TRUE)
private$..dep <- jmvcore::OptionVariable$new(
"dep",
dep,
default=NULL,
permitted=list(
"factor",
"numeric"))
private$..dep2 <- jmvcore::OptionVariable$new(
"dep2",
dep2,
default=NULL,
permitted=list(
"factor",
"numeric"))
private$..factors <- jmvcore::OptionVariables$new(
"factors",
factors,
suggested=list(
"nominal"),
permitted=list(
"factor"),
default=NULL)
private$..covs <- jmvcore::OptionVariables$new(
"covs",
covs,
suggested=list(
"continuous",
"ordinal"),
permitted=list(
"numeric"),
default=NULL)
private$..offset <- jmvcore::OptionVariable$new(
"offset",
offset,
default=NULL)
private$..model_terms <- jmvcore::OptionTerms$new(
"model_terms",
model_terms,
default=NULL)
private$..fixed_intercept <- jmvcore::OptionBool$new(
"fixed_intercept",
fixed_intercept,
default=TRUE)
private$..nested_intercept <- jmvcore::OptionBool$new(
"nested_intercept",
nested_intercept,
default=TRUE)
private$..nested_terms <- jmvcore::OptionTerms$new(
"nested_terms",
nested_terms,
default=NULL)
private$..comparison <- jmvcore::OptionBool$new(
"comparison",
comparison,
default=FALSE)
private$..estimates_ci <- jmvcore::OptionBool$new(
"estimates_ci",
estimates_ci,
default=FALSE)
private$..donotrun <- jmvcore::OptionBool$new(
"donotrun",
donotrun,
default=FALSE)
private$..input_method <- jmvcore::OptionList$new(
"input_method",
input_method,
default="standard",
options=list(
"standard",
"success",
"total"))
private$..ci_method <- jmvcore::OptionList$new(
"ci_method",
ci_method,
default="wald",
options=list(
"wald",
"profile",
"quantile",
"bcai"))
private$..boot_r <- jmvcore::OptionNumber$new(
"boot_r",
boot_r,
min=1,
default=1000)
private$..ci_width <- jmvcore::OptionNumber$new(
"ci_width",
ci_width,
min=50,
max=99.9,
default=95)
private$..contrasts <- jmvcore::OptionArray$new(
"contrasts",
contrasts,
items="(factors)",
default=NULL,
template=jmvcore::OptionGroup$new(
"contrasts",
NULL,
elements=list(
jmvcore::OptionVariable$new(
"var",
NULL,
content="$key"),
jmvcore::OptionList$new(
"type",
NULL,
options=list(
"simple",
"deviation",
"dummy",
"difference",
"helmert",
"repeated",
"polynomial"),
default="simple"))))
private$..show_contrastnames <- jmvcore::OptionBool$new(
"show_contrastnames",
show_contrastnames,
default=FALSE)
private$..show_contrastcodes <- jmvcore::OptionBool$new(
"show_contrastcodes",
show_contrastcodes,
default=FALSE)
private$..vcov <- jmvcore::OptionBool$new(
"vcov",
vcov,
default=FALSE)
private$..crosstab <- jmvcore::OptionBool$new(
"crosstab",
crosstab,
default=FALSE)
private$..plot_x <- jmvcore::OptionVariable$new(
"plot_x",
plot_x,
default=NULL)
private$..plot_z <- jmvcore::OptionVariable$new(
"plot_z",
plot_z,
default=NULL)
private$..plot_by <- jmvcore::OptionVariables$new(
"plot_by",
plot_by,
default=NULL)
private$..plot_raw <- jmvcore::OptionBool$new(
"plot_raw",
plot_raw,
default=FALSE)
private$..plot_yscale <- jmvcore::OptionBool$new(
"plot_yscale",
plot_yscale,
default=FALSE)
private$..plot_xoriginal <- jmvcore::OptionBool$new(
"plot_xoriginal",
plot_xoriginal,
default=FALSE)
private$..plot_black <- jmvcore::OptionBool$new(
"plot_black",
plot_black,
default=FALSE)
private$..plot_around <- jmvcore::OptionList$new(
"plot_around",
plot_around,
options=list(
"none",
"ci",
"se"),
default="ci")
private$..emmeans <- jmvcore::OptionTerms$new(
"emmeans",
emmeans,
default=NULL)
private$..posthoc <- jmvcore::OptionTerms$new(
"posthoc",
posthoc,
default=NULL)
private$..posthoc_ci <- jmvcore::OptionBool$new(
"posthoc_ci",
posthoc_ci,
default=FALSE)
private$..simple_x <- jmvcore::OptionVariable$new(
"simple_x",
simple_x,
default=NULL)
private$..simple_mods <- jmvcore::OptionVariables$new(
"simple_mods",
simple_mods,
default=NULL)
private$..simple_interactions <- jmvcore::OptionBool$new(
"simple_interactions",
simple_interactions,
default=FALSE)
private$..covs_conditioning <- jmvcore::OptionList$new(
"covs_conditioning",
covs_conditioning,
options=list(
"mean_sd",
"percent",
"range"),
default="mean_sd")
private$..ccra_steps <- jmvcore::OptionNumber$new(
"ccra_steps",
ccra_steps,
default=1,
min=1,
max=50)
private$..ccm_value <- jmvcore::OptionNumber$new(
"ccm_value",
ccm_value,
default=1)
private$..ccp_value <- jmvcore::OptionNumber$new(
"ccp_value",
ccp_value,
default=25,
min=5,
max=50)
private$..covs_scale_labels <- jmvcore::OptionList$new(
"covs_scale_labels",
covs_scale_labels,
options=list(
"labels",
"values",
"values_labels",
"uvalues",
"uvalues_labels"),
default="labels")
private$..adjust <- jmvcore::OptionNMXList$new(
"adjust",
adjust,
options=list(
"none",
"bonf",
"tukey",
"holm",
"scheffe",
"sidak"),
default=list(
"bonf"))
private$..predicted <- jmvcore::OptionOutput$new(
"predicted")
private$..residuals <- jmvcore::OptionOutput$new(
"residuals")
private$..covs_scale <- jmvcore::OptionArray$new(
"covs_scale",
covs_scale,
items="(covs)",
default=NULL,
template=jmvcore::OptionGroup$new(
"covs_scale",
NULL,
elements=list(
jmvcore::OptionVariable$new(
"var",
NULL,
content="$key"),
jmvcore::OptionList$new(
"type",
NULL,
options=list(
"centered",
"standardized",
"none"),
default="centered"))))
private$..scale_missing <- jmvcore::OptionList$new(
"scale_missing",
scale_missing,
options=list(
"complete",
"colwise"),
default="complete")
private$..mute <- jmvcore::OptionBool$new(
"mute",
mute,
default=FALSE)
private$..expb_ci <- jmvcore::OptionBool$new(
"expb_ci",
expb_ci,
default=TRUE)
private$..es <- jmvcore::OptionNMXList$new(
"es",
es,
options=list(
"expb",
"RR",
"marginals"),
default=list(
"expb"))
private$..model_type <- jmvcore::OptionList$new(
"model_type",
model_type,
options=list(
"linear",
"poisson",
"poiover",
"nb",
"logistic",
"probit",
"probit",
"beta",
"ordinal",
"multinomial",
"custom"),
default="linear")
private$..custom_family <- jmvcore::OptionList$new(
"custom_family",
custom_family,
options=list(
"gaussian",
"binomial",
"poisson",
"inverse.gaussian",
"Gamma"),
default="gaussian")
private$..custom_link <- jmvcore::OptionList$new(
"custom_link",
custom_link,
options=list(
"identity",
"logit",
"log",
"inverse",
"1/mu^2",
"sqrt"),
default="identity")
private$..propodds_test <- jmvcore::OptionBool$new(
"propodds_test",
propodds_test,
default=FALSE)
private$..preds_phi <- jmvcore::OptionBool$new(
"preds_phi",
preds_phi,
default=FALSE)
private$..plot_scale <- jmvcore::OptionList$new(
"plot_scale",
plot_scale,
options=list(
"response",
"link",
"mean.class"),
default="response")
self$.addOption(private$...caller)
self$.addOption(private$...interface)
self$.addOption(private$..dep)
self$.addOption(private$..dep2)
self$.addOption(private$..factors)
self$.addOption(private$..covs)
self$.addOption(private$..offset)
self$.addOption(private$..model_terms)
self$.addOption(private$..fixed_intercept)
self$.addOption(private$..nested_intercept)
self$.addOption(private$..nested_terms)
self$.addOption(private$..comparison)
self$.addOption(private$..estimates_ci)
self$.addOption(private$..donotrun)
self$.addOption(private$..input_method)
self$.addOption(private$..ci_method)
self$.addOption(private$..boot_r)
self$.addOption(private$..ci_width)
self$.addOption(private$..contrasts)
self$.addOption(private$..show_contrastnames)
self$.addOption(private$..show_contrastcodes)
self$.addOption(private$..vcov)
self$.addOption(private$..crosstab)
self$.addOption(private$..plot_x)
self$.addOption(private$..plot_z)
self$.addOption(private$..plot_by)
self$.addOption(private$..plot_raw)
self$.addOption(private$..plot_yscale)
self$.addOption(private$..plot_xoriginal)
self$.addOption(private$..plot_black)
self$.addOption(private$..plot_around)
self$.addOption(private$..emmeans)
self$.addOption(private$..posthoc)
self$.addOption(private$..posthoc_ci)
self$.addOption(private$..simple_x)
self$.addOption(private$..simple_mods)
self$.addOption(private$..simple_interactions)
self$.addOption(private$..covs_conditioning)
self$.addOption(private$..ccra_steps)
self$.addOption(private$..ccm_value)
self$.addOption(private$..ccp_value)
self$.addOption(private$..covs_scale_labels)
self$.addOption(private$..adjust)
self$.addOption(private$..predicted)
self$.addOption(private$..residuals)
self$.addOption(private$..covs_scale)
self$.addOption(private$..scale_missing)
self$.addOption(private$..mute)
self$.addOption(private$..expb_ci)
self$.addOption(private$..es)
self$.addOption(private$..model_type)
self$.addOption(private$..custom_family)
self$.addOption(private$..custom_link)
self$.addOption(private$..propodds_test)
self$.addOption(private$..preds_phi)
self$.addOption(private$..plot_scale)
}),
active = list(
.caller = function() private$...caller$value,
.interface = function() private$...interface$value,
dep = function() private$..dep$value,
dep2 = function() private$..dep2$value,
factors = function() private$..factors$value,
covs = function() private$..covs$value,
offset = function() private$..offset$value,
model_terms = function() private$..model_terms$value,
fixed_intercept = function() private$..fixed_intercept$value,
nested_intercept = function() private$..nested_intercept$value,
nested_terms = function() private$..nested_terms$value,
comparison = function() private$..comparison$value,
estimates_ci = function() private$..estimates_ci$value,
donotrun = function() private$..donotrun$value,
input_method = function() private$..input_method$value,
ci_method = function() private$..ci_method$value,
boot_r = function() private$..boot_r$value,
ci_width = function() private$..ci_width$value,
contrasts = function() private$..contrasts$value,
show_contrastnames = function() private$..show_contrastnames$value,
show_contrastcodes = function() private$..show_contrastcodes$value,
vcov = function() private$..vcov$value,
crosstab = function() private$..crosstab$value,
plot_x = function() private$..plot_x$value,
plot_z = function() private$..plot_z$value,
plot_by = function() private$..plot_by$value,
plot_raw = function() private$..plot_raw$value,
plot_yscale = function() private$..plot_yscale$value,
plot_xoriginal = function() private$..plot_xoriginal$value,
plot_black = function() private$..plot_black$value,
plot_around = function() private$..plot_around$value,
emmeans = function() private$..emmeans$value,
posthoc = function() private$..posthoc$value,
posthoc_ci = function() private$..posthoc_ci$value,
simple_x = function() private$..simple_x$value,
simple_mods = function() private$..simple_mods$value,
simple_interactions = function() private$..simple_interactions$value,
covs_conditioning = function() private$..covs_conditioning$value,
ccra_steps = function() private$..ccra_steps$value,
ccm_value = function() private$..ccm_value$value,
ccp_value = function() private$..ccp_value$value,
covs_scale_labels = function() private$..covs_scale_labels$value,
adjust = function() private$..adjust$value,
predicted = function() private$..predicted$value,
residuals = function() private$..residuals$value,
covs_scale = function() private$..covs_scale$value,
scale_missing = function() private$..scale_missing$value,
mute = function() private$..mute$value,
expb_ci = function() private$..expb_ci$value,
es = function() private$..es$value,
model_type = function() private$..model_type$value,
custom_family = function() private$..custom_family$value,
custom_link = function() private$..custom_link$value,
propodds_test = function() private$..propodds_test$value,
preds_phi = function() private$..preds_phi$value,
plot_scale = function() private$..plot_scale$value),
private = list(
...caller = NA,
...interface = NA,
..dep = NA,
..dep2 = NA,
..factors = NA,
..covs = NA,
..offset = NA,
..model_terms = NA,
..fixed_intercept = NA,
..nested_intercept = NA,
..nested_terms = NA,
..comparison = NA,
..estimates_ci = NA,
..donotrun = NA,
..input_method = NA,
..ci_method = NA,
..boot_r = NA,
..ci_width = NA,
..contrasts = NA,
..show_contrastnames = NA,
..show_contrastcodes = NA,
..vcov = NA,
..crosstab = NA,
..plot_x = NA,
..plot_z = NA,
..plot_by = NA,
..plot_raw = NA,
..plot_yscale = NA,
..plot_xoriginal = NA,
..plot_black = NA,
..plot_around = NA,
..emmeans = NA,
..posthoc = NA,
..posthoc_ci = NA,
..simple_x = NA,
..simple_mods = NA,
..simple_interactions = NA,
..covs_conditioning = NA,
..ccra_steps = NA,
..ccm_value = NA,
..ccp_value = NA,
..covs_scale_labels = NA,
..adjust = NA,
..predicted = NA,
..residuals = NA,
..covs_scale = NA,
..scale_missing = NA,
..mute = NA,
..expb_ci = NA,
..es = NA,
..model_type = NA,
..custom_family = NA,
..custom_link = NA,
..propodds_test = NA,
..preds_phi = NA,
..plot_scale = NA)
)
gamljglmResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"gamljglmResults",
inherit = jmvcore::Group,
active = list(
model = function() private$..model,
info = function() private$.items[["info"]],
main = function() private$.items[["main"]],
posthoc = function() private$.items[["posthoc"]],
simpleEffects = function() private$.items[["simpleEffects"]],
simpleInteractions = function() private$.items[["simpleInteractions"]],
emmeans = function() private$.items[["emmeans"]],
mainPlots = function() private$.items[["mainPlots"]],
plotnotes = function() private$.items[["plotnotes"]],
predicted = function() private$.items[["predicted"]],
residuals = function() private$.items[["residuals"]]),
private = list(
..model = NA),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Generalized Linear Model")
private$..model <- NULL
self$add(jmvcore::Table$new(
options=options,
name="info",
title="Model Info",
columns=list(
list(
`name`="info",
`type`="text",
`title`="Info"),
list(
`name`="value",
`type`="text",
`title`=""),
list(
`name`="specs",
`type`="text",
`title`="")),
refs="gamlj"))
self$add(R6::R6Class(
inherit = jmvcore::Group,
active = list(
r2 = function() private$.items[["r2"]],
fit = function() private$.items[["fit"]],
crosstab = function() private$.items[["crosstab"]],
anova = function() private$.items[["anova"]],
coefficients = function() private$.items[["coefficients"]],
phi = function() private$.items[["phi"]],
vcov = function() private$.items[["vcov"]],
contrastCodeTables = function() private$.items[["contrastCodeTables"]],
marginals = function() private$.items[["marginals"]],
relativerisk = function() private$.items[["relativerisk"]],
paralleltest = function() private$.items[["paralleltest"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="main",
title="Model Results")
self$add(jmvcore::Table$new(
options=options,
name="r2",
title="Model Fit",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"nested_terms",
"nested_intercept",
"comparison"),
rows=1,
columns=list(
list(
`name`="model",
`title`="Model",
`visible`="(comparison)"),
list(
`name`="r2",
`title`="R\u00B2",
`type`="number"),
list(
`name`="ar2",
`title`="Adj. R\u00B2",
`type`="number"),
list(
`name`="df1",
`title`="df",
`type`="integer"),
list(
`name`="test",
`title`="X\u00B2",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue")),
refs="goodness"))
self$add(jmvcore::Table$new(
options=options,
name="fit",
title="Additional indices",
visible=TRUE,
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link"),
columns=list(
list(
`name`="info",
`type`="text",
`title`="Info"),
list(
`name`="value",
`type`="text",
`title`="Model Value"),
list(
`name`="nested",
`type`="text",
`title`="Nested Model",
`visible`="(comparison)"),
list(
`name`="diff",
`type`="text",
`title`="\u0394",
`visible`="(comparison)"),
list(
`name`="specs",
`type`="text",
`title`="Comment"))))
self$add(jmvcore::Table$new(
options=options,
name="crosstab",
title="Classification table",
visible="(crosstab)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link"),
columns=list(
list(
`name`="obs",
`title`="Observed",
`type`="integer"))))
self$add(jmvcore::Table$new(
options=options,
name="anova",
title="Omnibus tests",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link"),
columns=list(
list(
`name`="source",
`title`="",
`type`="text"),
list(
`name`="test",
`title`="X\u00B2",
`type`="number"),
list(
`name`="df",
`title`="df",
`type`="integer"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="coefficients",
title="Parameter Estimates (Coefficients)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"ci_width",
"ci_method",
"boot_r"),
columns=list(
list(
`name`="response",
`title`="Response",
`type`="text",
`visible`="(model_type:multinomial)",
`combineBelow`=TRUE),
list(
`name`="source",
`title`="Name",
`type`="text"),
list(
`name`="label",
`title`="Effect",
`type`="text",
`visible`="(show_contrastnames)"),
list(
`name`="estimate",
`title`="Estimate",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(estimates_ci)"),
list(
`name`="est.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(estimates_ci)"),
list(
`name`="expb",
`type`="number",
`title`="Exp(B)",
`visible`="(es:expb)"),
list(
`name`="expb.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(es:expb & expb_ci)"),
list(
`name`="expb.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(es:expb & expb_ci)"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="phi",
title="Precision Parameter Estimates (phi)",
visible="(model_type:beta)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"ci_width",
"ci_method",
"boot_r"),
columns=list(
list(
`name`="source",
`title`="Name",
`type`="text"),
list(
`name`="label",
`title`="Effect",
`type`="text",
`visible`="(show_contrastnames)"),
list(
`name`="estimate",
`title`="Estimate",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`type`="number",
`title`="Lower"),
list(
`name`="est.ci.upper",
`type`="number",
`title`="Upper"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="vcov",
title="Coefficients Covariances",
visible="(vcov)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link"),
columns=list(
list(
`name`="source",
`title`="Coefficient",
`type`="text",
`visible`="(show_contrastnames)"))))
self$add(jmvcore::Array$new(
options=options,
name="contrastCodeTables",
title="Contrast Coefficients",
visible="(show_contrastcodes)",
items="(factors)",
clearWith=list(
"contrasts"),
template=jmvcore::Table$new(
options=options,
title="$key",
columns=list(
list(
`name`="cname",
`title`="Name",
`type`="text",
`visible`="(show_contrastnames)"),
list(
`name`="clab",
`title`="Contrast",
`type`="text"),
list(
`name`="bogus",
`title`="bogus",
`type`="text",
`visible`=FALSE)))))
self$add(jmvcore::Table$new(
options=options,
name="marginals",
title="Marginal Effects",
visible="(es:marginals)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"simple_x",
"simple_mods",
"simple_scale",
"ccm_value",
"ccp_value",
"ccra_steps",
"covs_scale_labels",
"covs_conditioning"),
columns=list(
list(
`name`="response",
`title`="Response",
`type`="text",
`combineBelow`=TRUE,
`visible`="(model_type:multinomial)"),
list(
`name`="source",
`title`="Name",
`type`="text"),
list(
`name`="contrast",
`title`="Effect",
`type`="text"),
list(
`name`="estimate",
`title`="AME",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(expb_ci | estimates_ci)"),
list(
`name`="est.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(expb_ci | estimates_ci)"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="relativerisk",
title="Relative risk",
visible="(es:RR)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"__effectsizeoptions"),
columns=list(
list(
`name`="source",
`title`="Name",
`type`="text",
`visible`="(show_contrastnames)"),
list(
`name`="label",
`title`="Effect",
`type`="text"),
list(
`name`="estimate",
`title`="RR",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(expb_ci | estimates_ci)"),
list(
`name`="est.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(expb_ci | estimates_ci)"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="paralleltest",
title="Parallel lines test",
visible="(propodds_test & model_type:ordinal)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"propodds_test"),
columns=list(
list(
`name`="source",
`title`="",
`type`="text"),
list(
`name`="loglik",
`title`="Log-Lik.",
`type`="number"),
list(
`name`="aic",
`title`="AIC",
`type`="number"),
list(
`name`="test",
`title`="X\u00B2",
`type`="number"),
list(
`name`="df",
`title`="df",
`type`="integer"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))}))$new(options=options))
self$add(jmvcore::Array$new(
options=options,
name="posthoc",
title="Post Hoc Tests",
items="(posthoc)",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"posthoc",
"adjust",
"ci_width",
"ci_method",
"boot_r"),
template=jmvcore::Table$new(
options=options,
title="",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"posthoc",
"adjust",
"ci_width",
"ci_method",
"boot_r"),
columns=list(
list(
`name`="response",
`title`="Response",
`type`="text",
`visible`="(model_type:multinomial)",
`combineBelow`=TRUE),
list(
`name`="estimate",
`title`="Difference",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(posthoc_ci)"),
list(
`name`="est.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(posthoc_ci)"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="none",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(adjust:none)"),
list(
`name`="bonf",
`title`="p<sub>bonferroni</sub>",
`type`="number",
`format`="zto,pvalue",
`visible`="(adjust:bonf)"),
list(
`name`="tukey",
`title`="p<sub>tukey</sub>",
`type`="number",
`format`="zto,pvalue",
`visible`="(adjust:tukey)"),
list(
`name`="holm",
`title`="p<sub>holm</sub>",
`type`="number",
`format`="zto,pvalue",
`visible`="(adjust:holm)")))))
self$add(R6::R6Class(
inherit = jmvcore::Group,
active = list(
anova = function() private$.items[["anova"]],
coefficients = function() private$.items[["coefficients"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="simpleEffects",
title="Simple Effects")
self$add(jmvcore::Table$new(
options=options,
name="anova",
title="ANOVA for Simple Effects of ___key___",
visible=FALSE,
clearWith=list(
"dep",
"model_terms",
"contrasts",
"covs_conditioning",
"fixed_intercept",
"simple_effects",
"simple_moderators",
"covs_scale",
"ccm_value",
"ccp_value",
"covs_scale_labels",
"offset"),
columns=list(
list(
`name`="test",
`title`="X\u00B2",
`type`="number"),
list(
`name`="df1",
`title`="df",
`type`="integer"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="coefficients",
title="Parameter Estimates for simple effects of ___key___",
visible=FALSE,
clearWith=list(
"dep",
"model_terms",
"contrasts",
"covs_conditioning",
"dep_scale",
"fixed_intercept",
"simple_effects",
"simple_moderators",
"covs_scale",
"ccm_value",
"ccp_value",
"covs_scale_labels",
"ci_method",
"boot_r",
"offset"),
columns=list(
list(
`name`="response",
`title`="Response",
`type`="text",
`combineBelow`=TRUE,
`visible`="(model_type:multinomial)"),
list(
`name`="contrast",
`title`="Effect",
`type`="text"),
list(
`name`="estimate",
`title`="Estimate",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(estimates_ci)"),
list(
`name`="est.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(estimates_ci)"),
list(
`name`="expb",
`type`="number",
`title`="Exp(B)",
`visible`="(es:expb)"),
list(
`name`="expb.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(expb_ci)"),
list(
`name`="expb.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(expb_ci)"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))}))$new(options=options))
self$add(jmvcore::Array$new(
options=options,
name="simpleInteractions",
title="Simple Interactions",
visible=FALSE,
clearWith=list(
"dep",
"model_terms",
"contrasts",
"covs_conditioning",
"dep_scale",
"fixed_intercept",
"covs_scale_labels",
"ci_width",
"emmeans",
"offset"),
template=R6::R6Class(
inherit = jmvcore::Group,
active = list(
anova = function() private$.items[["anova"]],
coefficients = function() private$.items[["coefficients"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="undefined",
title="Interaction: ___key___",
clearWith=list())
self$add(jmvcore::Table$new(
options=options,
name="anova",
title="ANOVA test - $key",
columns=list(
list(
`name`="effect",
`title`="Effect",
`type`="text"),
list(
`name`="test",
`title`="X\u00B2",
`type`="number"),
list(
`name`="df1",
`title`="df",
`type`="integer"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="coefficients",
title="Parameter Estimates for - $key",
columns=list(
list(
`name`="effect",
`title`="Effect",
`type`="text"),
list(
`name`="response",
`title`="Response",
`type`="text",
`visible`="(model_type:multinomial)"),
list(
`name`="estimate",
`title`="Estimate",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`title`="Lower",
`type`="number"),
list(
`name`="est.ci.upper",
`title`="Upper",
`type`="number"),
list(
`name`="test",
`title`="z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"),
list(
`name`="expb",
`type`="number",
`title`="Exp(B)",
`visible`="(es:expb)"),
list(
`name`="expb.ci.lower",
`type`="number",
`title`="Lower",
`visible`="(expb_ci)",
`superTitle`="Exp(B) Confidence Intervals"),
list(
`name`="expb.ci.upper",
`type`="number",
`title`="Upper",
`visible`="(expb_ci)",
`superTitle`="Exp(B) Confidence Intervals"))))}))$new(options=options)))
self$add(jmvcore::Array$new(
options=options,
name="emmeans",
title="Estimated Marginal Means",
visible=FALSE,
items="(emmeans)",
template=jmvcore::Table$new(
options=options,
title="Estimate Marginal Means - ___key___",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link",
"ci_width",
"ci_method",
"boot_r"),
columns=list(
list(
`name`="response",
`title`="Response",
`type`="text",
`visible`="(model_type:multinomial)",
`combineBelow`=TRUE),
list(
`name`="estimate",
`title`="Mean",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="est.ci.lower",
`title`="Lower",
`type`="number"),
list(
`name`="est.ci.upper",
`title`="Upper",
`type`="number")))))
self$add(jmvcore::Array$new(
options=options,
name="mainPlots",
title="Results Plots",
template=jmvcore::Image$new(
options=options,
title="",
renderFun=".mainPlot",
width=600,
height=400,
clearWith=list(
"dep",
"plot_x",
"plot_z",
"plot_by",
"plot_raw",
"plot_yscale",
"plot_scale",
"plot_xoriginal",
"plot_black",
"plot_around",
"ci_width",
"covs_scale",
"dep_scale",
"model_terms",
"fixed_intercept",
"covs_conditioning",
"covs_scale_labels",
"ccp_value",
"ccm_value"))))
self$add(jmvcore::Html$new(
options=options,
name="plotnotes",
visible=FALSE))
self$add(jmvcore::Output$new(
options=options,
name="predicted",
title="Predicted Vales",
varTitle="`GLM_${ dep }_PRED`",
varDescription="Predicted values",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link")))
self$add(jmvcore::Output$new(
options=options,
name="residuals",
title="Residuals Vales",
varTitle="`GLM_${ dep }_RES`",
varDescription="Residuals values",
clearWith=list(
"model_type",
"dep",
"dep2",
"factors",
"covs",
"covs_scale",
"scale_missing",
"model_terms",
"fixed_intercept",
"se_method",
"mute",
"df_method",
"contrasts",
"covs_scale",
"offset",
"omnibus",
"model_type",
"custom_family",
"custom_link")))},
.setModel=function(x) private$..model <- x))
gamljglmBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"gamljglmBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "GAMLj3",
name = "gamljglm",
version = c(3,0,0),
options = options,
results = gamljglmResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE,
requiresMissings = FALSE,
weightsSupport = 'none')
}))
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