R/umbrella.h.R
In CorentinJGosling/metaumbrella_jmv: Umbrella Review Module for Jamovi
# This file is automatically generated, you probably don't want to edit this
umbrellaOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"umbrellaOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
vars = NULL,
criteria = "Ioannidis",
method.var = "REML",
pre_post_cor = 0.5,
true_effect = "largest",
method.esb = "TESSPSST",
mult.level = FALSE,
r = 0.8,
n_studies_1 = NULL,
n_studies_2 = NULL,
n_studies_3 = NULL,
n_studies_4 = NULL,
total_n_1 = NULL,
total_n_2 = NULL,
total_n_3 = NULL,
total_n_4 = NULL,
n_cases_1 = NULL,
n_cases_2 = NULL,
n_cases_3 = NULL,
n_cases_4 = NULL,
p_value_1 = NULL,
p_value_2 = NULL,
p_value_3 = NULL,
p_value_4 = NULL,
I2_1 = NULL,
I2_2 = NULL,
I2_3 = NULL,
I2_4 = NULL,
imprecision_1 = NULL,
imprecision_2 = NULL,
imprecision_3 = NULL,
imprecision_4 = NULL,
rob_1 = NULL,
rob_2 = NULL,
rob_3 = NULL,
rob_4 = NULL,
amstar_1 = NULL,
amstar_2 = NULL,
amstar_3 = NULL,
amstar_4 = NULL,
egger_p_1 = NULL,
egger_p_2 = NULL,
egger_p_3 = NULL,
egger_p_4 = NULL,
esb_p_1 = NULL,
esb_p_2 = NULL,
esb_p_3 = NULL,
esb_p_4 = NULL,
JK_p_1 = NULL,
JK_p_2 = NULL,
JK_p_3 = NULL,
JK_p_4 = NULL,
pi_1 = FALSE,
pi_2 = FALSE,
pi_3 = FALSE,
pi_4 = FALSE,
largest_CI_1 = FALSE,
largest_CI_2 = FALSE,
largest_CI_3 = FALSE,
largest_CI_4 = FALSE,
measure_forest = "eG",
class_forest = "no_rest",
title_forest = NULL,
title_xaxis = NULL,
cex = 1,
cex_dot = 1,
x_lim_adj = 0,
y_lim_adj = 0,
max_x = 2,
x_axis_adj = 0, ...) {
super$initialize(
package="metaumbrella",
name="umbrella",
requiresData=TRUE,
...)
private$..vars <- jmvcore::OptionVariables$new(
"vars",
vars,
takeFromDataIfMissing=TRUE,
permitted=list(
"numeric",
"factor",
"id"))
private$..criteria <- jmvcore::OptionList$new(
"criteria",
criteria,
options=list(
"Ioannidis",
"GRADE",
"Personalized",
"None"),
default="Ioannidis")
private$..method.var <- jmvcore::OptionList$new(
"method.var",
method.var,
options=list(
"REML",
"DL",
"hksj",
"ML",
"PM",
"FE"),
default="REML")
private$..pre_post_cor <- jmvcore::OptionNumber$new(
"pre_post_cor",
pre_post_cor,
min=0,
max=1,
default=0.5)
private$..true_effect <- jmvcore::OptionList$new(
"true_effect",
true_effect,
options=list(
"largest",
"pooled",
"UWLS"),
default="largest")
private$..method.esb <- jmvcore::OptionList$new(
"method.esb",
method.esb,
options=list(
"IT.binom",
"IT.chisq",
"TESS",
"PSST",
"TESSPSST"),
default="TESSPSST")
private$..mult.level <- jmvcore::OptionBool$new(
"mult.level",
mult.level,
default=FALSE)
private$..r <- jmvcore::OptionNumber$new(
"r",
r,
min=0,
max=1,
default=0.8)
private$..n_studies_1 <- jmvcore::OptionString$new(
"n_studies_1",
n_studies_1)
private$..n_studies_2 <- jmvcore::OptionString$new(
"n_studies_2",
n_studies_2)
private$..n_studies_3 <- jmvcore::OptionString$new(
"n_studies_3",
n_studies_3)
private$..n_studies_4 <- jmvcore::OptionString$new(
"n_studies_4",
n_studies_4)
private$..total_n_1 <- jmvcore::OptionString$new(
"total_n_1",
total_n_1)
private$..total_n_2 <- jmvcore::OptionString$new(
"total_n_2",
total_n_2)
private$..total_n_3 <- jmvcore::OptionString$new(
"total_n_3",
total_n_3)
private$..total_n_4 <- jmvcore::OptionString$new(
"total_n_4",
total_n_4)
private$..n_cases_1 <- jmvcore::OptionString$new(
"n_cases_1",
n_cases_1)
private$..n_cases_2 <- jmvcore::OptionString$new(
"n_cases_2",
n_cases_2)
private$..n_cases_3 <- jmvcore::OptionString$new(
"n_cases_3",
n_cases_3)
private$..n_cases_4 <- jmvcore::OptionString$new(
"n_cases_4",
n_cases_4)
private$..p_value_1 <- jmvcore::OptionString$new(
"p_value_1",
p_value_1)
private$..p_value_2 <- jmvcore::OptionString$new(
"p_value_2",
p_value_2)
private$..p_value_3 <- jmvcore::OptionString$new(
"p_value_3",
p_value_3)
private$..p_value_4 <- jmvcore::OptionString$new(
"p_value_4",
p_value_4)
private$..I2_1 <- jmvcore::OptionString$new(
"I2_1",
I2_1)
private$..I2_2 <- jmvcore::OptionString$new(
"I2_2",
I2_2)
private$..I2_3 <- jmvcore::OptionString$new(
"I2_3",
I2_3)
private$..I2_4 <- jmvcore::OptionString$new(
"I2_4",
I2_4)
private$..imprecision_1 <- jmvcore::OptionString$new(
"imprecision_1",
imprecision_1)
private$..imprecision_2 <- jmvcore::OptionString$new(
"imprecision_2",
imprecision_2)
private$..imprecision_3 <- jmvcore::OptionString$new(
"imprecision_3",
imprecision_3)
private$..imprecision_4 <- jmvcore::OptionString$new(
"imprecision_4",
imprecision_4)
private$..rob_1 <- jmvcore::OptionString$new(
"rob_1",
rob_1)
private$..rob_2 <- jmvcore::OptionString$new(
"rob_2",
rob_2)
private$..rob_3 <- jmvcore::OptionString$new(
"rob_3",
rob_3)
private$..rob_4 <- jmvcore::OptionString$new(
"rob_4",
rob_4)
private$..amstar_1 <- jmvcore::OptionString$new(
"amstar_1",
amstar_1)
private$..amstar_2 <- jmvcore::OptionString$new(
"amstar_2",
amstar_2)
private$..amstar_3 <- jmvcore::OptionString$new(
"amstar_3",
amstar_3)
private$..amstar_4 <- jmvcore::OptionString$new(
"amstar_4",
amstar_4)
private$..egger_p_1 <- jmvcore::OptionString$new(
"egger_p_1",
egger_p_1)
private$..egger_p_2 <- jmvcore::OptionString$new(
"egger_p_2",
egger_p_2)
private$..egger_p_3 <- jmvcore::OptionString$new(
"egger_p_3",
egger_p_3)
private$..egger_p_4 <- jmvcore::OptionString$new(
"egger_p_4",
egger_p_4)
private$..esb_p_1 <- jmvcore::OptionString$new(
"esb_p_1",
esb_p_1)
private$..esb_p_2 <- jmvcore::OptionString$new(
"esb_p_2",
esb_p_2)
private$..esb_p_3 <- jmvcore::OptionString$new(
"esb_p_3",
esb_p_3)
private$..esb_p_4 <- jmvcore::OptionString$new(
"esb_p_4",
esb_p_4)
private$..JK_p_1 <- jmvcore::OptionString$new(
"JK_p_1",
JK_p_1)
private$..JK_p_2 <- jmvcore::OptionString$new(
"JK_p_2",
JK_p_2)
private$..JK_p_3 <- jmvcore::OptionString$new(
"JK_p_3",
JK_p_3)
private$..JK_p_4 <- jmvcore::OptionString$new(
"JK_p_4",
JK_p_4)
private$..pi_1 <- jmvcore::OptionBool$new(
"pi_1",
pi_1,
default=FALSE)
private$..pi_2 <- jmvcore::OptionBool$new(
"pi_2",
pi_2,
default=FALSE)
private$..pi_3 <- jmvcore::OptionBool$new(
"pi_3",
pi_3,
default=FALSE)
private$..pi_4 <- jmvcore::OptionBool$new(
"pi_4",
pi_4,
default=FALSE)
private$..largest_CI_1 <- jmvcore::OptionBool$new(
"largest_CI_1",
largest_CI_1,
default=FALSE)
private$..largest_CI_2 <- jmvcore::OptionBool$new(
"largest_CI_2",
largest_CI_2,
default=FALSE)
private$..largest_CI_3 <- jmvcore::OptionBool$new(
"largest_CI_3",
largest_CI_3,
default=FALSE)
private$..largest_CI_4 <- jmvcore::OptionBool$new(
"largest_CI_4",
largest_CI_4,
default=FALSE)
private$..measure_forest <- jmvcore::OptionList$new(
"measure_forest",
measure_forest,
options=list(
"eG",
"eOR"),
default="eG")
private$..class_forest <- jmvcore::OptionList$new(
"class_forest",
class_forest,
options=list(
"no_rest",
"I",
"II",
"III",
"IV",
"High",
"Moderate",
"Weak"),
default="no_rest")
private$..title_forest <- jmvcore::OptionString$new(
"title_forest",
title_forest)
private$..title_xaxis <- jmvcore::OptionString$new(
"title_xaxis",
title_xaxis)
private$..cex <- jmvcore::OptionNumber$new(
"cex",
cex,
min=0,
default=1)
private$..cex_dot <- jmvcore::OptionNumber$new(
"cex_dot",
cex_dot,
min=0,
default=1)
private$..x_lim_adj <- jmvcore::OptionNumber$new(
"x_lim_adj",
x_lim_adj,
default=0)
private$..y_lim_adj <- jmvcore::OptionNumber$new(
"y_lim_adj",
y_lim_adj,
default=0)
private$..max_x <- jmvcore::OptionNumber$new(
"max_x",
max_x,
default=2)
private$..x_axis_adj <- jmvcore::OptionNumber$new(
"x_axis_adj",
x_axis_adj,
default=0)
self$.addOption(private$..vars)
self$.addOption(private$..criteria)
self$.addOption(private$..method.var)
self$.addOption(private$..pre_post_cor)
self$.addOption(private$..true_effect)
self$.addOption(private$..method.esb)
self$.addOption(private$..mult.level)
self$.addOption(private$..r)
self$.addOption(private$..n_studies_1)
self$.addOption(private$..n_studies_2)
self$.addOption(private$..n_studies_3)
self$.addOption(private$..n_studies_4)
self$.addOption(private$..total_n_1)
self$.addOption(private$..total_n_2)
self$.addOption(private$..total_n_3)
self$.addOption(private$..total_n_4)
self$.addOption(private$..n_cases_1)
self$.addOption(private$..n_cases_2)
self$.addOption(private$..n_cases_3)
self$.addOption(private$..n_cases_4)
self$.addOption(private$..p_value_1)
self$.addOption(private$..p_value_2)
self$.addOption(private$..p_value_3)
self$.addOption(private$..p_value_4)
self$.addOption(private$..I2_1)
self$.addOption(private$..I2_2)
self$.addOption(private$..I2_3)
self$.addOption(private$..I2_4)
self$.addOption(private$..imprecision_1)
self$.addOption(private$..imprecision_2)
self$.addOption(private$..imprecision_3)
self$.addOption(private$..imprecision_4)
self$.addOption(private$..rob_1)
self$.addOption(private$..rob_2)
self$.addOption(private$..rob_3)
self$.addOption(private$..rob_4)
self$.addOption(private$..amstar_1)
self$.addOption(private$..amstar_2)
self$.addOption(private$..amstar_3)
self$.addOption(private$..amstar_4)
self$.addOption(private$..egger_p_1)
self$.addOption(private$..egger_p_2)
self$.addOption(private$..egger_p_3)
self$.addOption(private$..egger_p_4)
self$.addOption(private$..esb_p_1)
self$.addOption(private$..esb_p_2)
self$.addOption(private$..esb_p_3)
self$.addOption(private$..esb_p_4)
self$.addOption(private$..JK_p_1)
self$.addOption(private$..JK_p_2)
self$.addOption(private$..JK_p_3)
self$.addOption(private$..JK_p_4)
self$.addOption(private$..pi_1)
self$.addOption(private$..pi_2)
self$.addOption(private$..pi_3)
self$.addOption(private$..pi_4)
self$.addOption(private$..largest_CI_1)
self$.addOption(private$..largest_CI_2)
self$.addOption(private$..largest_CI_3)
self$.addOption(private$..largest_CI_4)
self$.addOption(private$..measure_forest)
self$.addOption(private$..class_forest)
self$.addOption(private$..title_forest)
self$.addOption(private$..title_xaxis)
self$.addOption(private$..cex)
self$.addOption(private$..cex_dot)
self$.addOption(private$..x_lim_adj)
self$.addOption(private$..y_lim_adj)
self$.addOption(private$..max_x)
self$.addOption(private$..x_axis_adj)
}),
active = list(
vars = function() private$..vars$value,
criteria = function() private$..criteria$value,
method.var = function() private$..method.var$value,
pre_post_cor = function() private$..pre_post_cor$value,
true_effect = function() private$..true_effect$value,
method.esb = function() private$..method.esb$value,
mult.level = function() private$..mult.level$value,
r = function() private$..r$value,
n_studies_1 = function() private$..n_studies_1$value,
n_studies_2 = function() private$..n_studies_2$value,
n_studies_3 = function() private$..n_studies_3$value,
n_studies_4 = function() private$..n_studies_4$value,
total_n_1 = function() private$..total_n_1$value,
total_n_2 = function() private$..total_n_2$value,
total_n_3 = function() private$..total_n_3$value,
total_n_4 = function() private$..total_n_4$value,
n_cases_1 = function() private$..n_cases_1$value,
n_cases_2 = function() private$..n_cases_2$value,
n_cases_3 = function() private$..n_cases_3$value,
n_cases_4 = function() private$..n_cases_4$value,
p_value_1 = function() private$..p_value_1$value,
p_value_2 = function() private$..p_value_2$value,
p_value_3 = function() private$..p_value_3$value,
p_value_4 = function() private$..p_value_4$value,
I2_1 = function() private$..I2_1$value,
I2_2 = function() private$..I2_2$value,
I2_3 = function() private$..I2_3$value,
I2_4 = function() private$..I2_4$value,
imprecision_1 = function() private$..imprecision_1$value,
imprecision_2 = function() private$..imprecision_2$value,
imprecision_3 = function() private$..imprecision_3$value,
imprecision_4 = function() private$..imprecision_4$value,
rob_1 = function() private$..rob_1$value,
rob_2 = function() private$..rob_2$value,
rob_3 = function() private$..rob_3$value,
rob_4 = function() private$..rob_4$value,
amstar_1 = function() private$..amstar_1$value,
amstar_2 = function() private$..amstar_2$value,
amstar_3 = function() private$..amstar_3$value,
amstar_4 = function() private$..amstar_4$value,
egger_p_1 = function() private$..egger_p_1$value,
egger_p_2 = function() private$..egger_p_2$value,
egger_p_3 = function() private$..egger_p_3$value,
egger_p_4 = function() private$..egger_p_4$value,
esb_p_1 = function() private$..esb_p_1$value,
esb_p_2 = function() private$..esb_p_2$value,
esb_p_3 = function() private$..esb_p_3$value,
esb_p_4 = function() private$..esb_p_4$value,
JK_p_1 = function() private$..JK_p_1$value,
JK_p_2 = function() private$..JK_p_2$value,
JK_p_3 = function() private$..JK_p_3$value,
JK_p_4 = function() private$..JK_p_4$value,
pi_1 = function() private$..pi_1$value,
pi_2 = function() private$..pi_2$value,
pi_3 = function() private$..pi_3$value,
pi_4 = function() private$..pi_4$value,
largest_CI_1 = function() private$..largest_CI_1$value,
largest_CI_2 = function() private$..largest_CI_2$value,
largest_CI_3 = function() private$..largest_CI_3$value,
largest_CI_4 = function() private$..largest_CI_4$value,
measure_forest = function() private$..measure_forest$value,
class_forest = function() private$..class_forest$value,
title_forest = function() private$..title_forest$value,
title_xaxis = function() private$..title_xaxis$value,
cex = function() private$..cex$value,
cex_dot = function() private$..cex_dot$value,
x_lim_adj = function() private$..x_lim_adj$value,
y_lim_adj = function() private$..y_lim_adj$value,
max_x = function() private$..max_x$value,
x_axis_adj = function() private$..x_axis_adj$value),
private = list(
..vars = NA,
..criteria = NA,
..method.var = NA,
..pre_post_cor = NA,
..true_effect = NA,
..method.esb = NA,
..mult.level = NA,
..r = NA,
..n_studies_1 = NA,
..n_studies_2 = NA,
..n_studies_3 = NA,
..n_studies_4 = NA,
..total_n_1 = NA,
..total_n_2 = NA,
..total_n_3 = NA,
..total_n_4 = NA,
..n_cases_1 = NA,
..n_cases_2 = NA,
..n_cases_3 = NA,
..n_cases_4 = NA,
..p_value_1 = NA,
..p_value_2 = NA,
..p_value_3 = NA,
..p_value_4 = NA,
..I2_1 = NA,
..I2_2 = NA,
..I2_3 = NA,
..I2_4 = NA,
..imprecision_1 = NA,
..imprecision_2 = NA,
..imprecision_3 = NA,
..imprecision_4 = NA,
..rob_1 = NA,
..rob_2 = NA,
..rob_3 = NA,
..rob_4 = NA,
..amstar_1 = NA,
..amstar_2 = NA,
..amstar_3 = NA,
..amstar_4 = NA,
..egger_p_1 = NA,
..egger_p_2 = NA,
..egger_p_3 = NA,
..egger_p_4 = NA,
..esb_p_1 = NA,
..esb_p_2 = NA,
..esb_p_3 = NA,
..esb_p_4 = NA,
..JK_p_1 = NA,
..JK_p_2 = NA,
..JK_p_3 = NA,
..JK_p_4 = NA,
..pi_1 = NA,
..pi_2 = NA,
..pi_3 = NA,
..pi_4 = NA,
..largest_CI_1 = NA,
..largest_CI_2 = NA,
..largest_CI_3 = NA,
..largest_CI_4 = NA,
..measure_forest = NA,
..class_forest = NA,
..title_forest = NA,
..title_xaxis = NA,
..cex = NA,
..cex_dot = NA,
..x_lim_adj = NA,
..y_lim_adj = NA,
..max_x = NA,
..x_axis_adj = NA)
)
umbrellaResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"umbrellaResults",
inherit = jmvcore::Group,
active = list(
text = function() private$.items[["text"]],
checktable = function() private$.items[["checktable"]],
strattable = function() private$.items[["strattable"]],
metatable = function() private$.items[["metatable"]],
addtable = function() private$.items[["addtable"]],
plot = function() private$.items[["plot"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Results of the umbrella review")
self$add(jmvcore::Html$new(
options=options,
name="text"))
self$add(jmvcore::Table$new(
options=options,
name="checktable",
title="List of problematic rows (if any)",
rows=1,
columns=list(
list(
`name`="Row",
`type`="text"),
list(
`name`="Type_errors",
`type`="text"),
list(
`name`="Description_errors",
`type`="text"),
list(
`name`="author",
`type`="text"),
list(
`name`="year",
`type`="text"))))
self$add(jmvcore::Table$new(
options=options,
name="strattable",
title="Summary results",
rows=1,
columns=list(
list(
`name`="Factor",
`type`="text"),
list(
`name`="Criteria",
`type`="text"),
list(
`name`="Class",
`type`="text"),
list(
`name`="n_studies",
`type`="text"),
list(
`name`="total_n",
`type`="text"),
list(
`name`="n_cases",
`type`="text"),
list(
`name`="n_controls",
`type`="text"))))
self$add(jmvcore::Table$new(
options=options,
name="metatable",
title="Core meta-analytic results",
rows=1,
columns=list(
list(
`name`="Factor",
`type`="text"),
list(
`name`="measure",
`type`="text"),
list(
`name`="value",
`type`="text",
`format`="zto"),
list(
`name`="value_CI",
`type`="text",
`format`="zto"),
list(
`name`="eG",
`type`="text",
`format`="zto"),
list(
`name`="eG_CI",
`type`="text",
`format`="zto"),
list(
`name`="eOR",
`type`="text",
`format`="zto"),
list(
`name`="eOR_CI",
`type`="text",
`format`="zto"),
list(
`name`="p_value",
`type`="text",
`format`="zto"))))
self$add(jmvcore::Table$new(
options=options,
name="addtable",
title="Additional results",
rows=1,
columns=list(
list(
`name`="Factor",
`type`="text"),
list(
`name`="I2",
`type`="text",
`format`="zto"),
list(
`name`="PI_eG",
`type`="text",
`format`="zto"),
list(
`name`="PI_eOR",
`type`="text",
`format`="zto"),
list(
`name`="egger_p",
`type`="text",
`format`="zto"),
list(
`name`="ESB_p",
`type`="text",
`format`="zto"),
list(
`name`="power_med",
`type`="text",
`format`="zto"),
list(
`name`="JK_p",
`type`="text",
`format`="zto"),
list(
`name`="largest_CI_eG",
`type`="text",
`format`="zto"),
list(
`name`="largest_CI_eOR",
`type`="text",
`format`="zto"),
list(
`name`="rob",
`type`="text",
`format`="zto"),
list(
`name`="amstar",
`type`="text",
`format`="zto"))))
self$add(jmvcore::Image$new(
options=options,
name="plot",
title="Forest Plot",
width=900,
height=900,
renderFun=".plot"))}))
umbrellaBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"umbrellaBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "metaumbrella",
name = "umbrella",
version = c(1,0,5),
options = options,
results = umbrellaResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE,
requiresMissings = FALSE)
}))
CorentinJGosling/metaumbrella_jmv documentation built on Aug. 30, 2022, 3:29 a.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
# This file is automatically generated, you probably don't want to edit this
umbrellaOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"umbrellaOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
vars = NULL,
criteria = "Ioannidis",
method.var = "REML",
pre_post_cor = 0.5,
true_effect = "largest",
method.esb = "TESSPSST",
mult.level = FALSE,
r = 0.8,
n_studies_1 = NULL,
n_studies_2 = NULL,
n_studies_3 = NULL,
n_studies_4 = NULL,
total_n_1 = NULL,
total_n_2 = NULL,
total_n_3 = NULL,
total_n_4 = NULL,
n_cases_1 = NULL,
n_cases_2 = NULL,
n_cases_3 = NULL,
n_cases_4 = NULL,
p_value_1 = NULL,
p_value_2 = NULL,
p_value_3 = NULL,
p_value_4 = NULL,
I2_1 = NULL,
I2_2 = NULL,
I2_3 = NULL,
I2_4 = NULL,
imprecision_1 = NULL,
imprecision_2 = NULL,
imprecision_3 = NULL,
imprecision_4 = NULL,
rob_1 = NULL,
rob_2 = NULL,
rob_3 = NULL,
rob_4 = NULL,
amstar_1 = NULL,
amstar_2 = NULL,
amstar_3 = NULL,
amstar_4 = NULL,
egger_p_1 = NULL,
egger_p_2 = NULL,
egger_p_3 = NULL,
egger_p_4 = NULL,
esb_p_1 = NULL,
esb_p_2 = NULL,
esb_p_3 = NULL,
esb_p_4 = NULL,
JK_p_1 = NULL,
JK_p_2 = NULL,
JK_p_3 = NULL,
JK_p_4 = NULL,
pi_1 = FALSE,
pi_2 = FALSE,
pi_3 = FALSE,
pi_4 = FALSE,
largest_CI_1 = FALSE,
largest_CI_2 = FALSE,
largest_CI_3 = FALSE,
largest_CI_4 = FALSE,
measure_forest = "eG",
class_forest = "no_rest",
title_forest = NULL,
title_xaxis = NULL,
cex = 1,
cex_dot = 1,
x_lim_adj = 0,
y_lim_adj = 0,
max_x = 2,
x_axis_adj = 0, ...) {
super$initialize(
package="metaumbrella",
name="umbrella",
requiresData=TRUE,
...)
private$..vars <- jmvcore::OptionVariables$new(
"vars",
vars,
takeFromDataIfMissing=TRUE,
permitted=list(
"numeric",
"factor",
"id"))
private$..criteria <- jmvcore::OptionList$new(
"criteria",
criteria,
options=list(
"Ioannidis",
"GRADE",
"Personalized",
"None"),
default="Ioannidis")
private$..method.var <- jmvcore::OptionList$new(
"method.var",
method.var,
options=list(
"REML",
"DL",
"hksj",
"ML",
"PM",
"FE"),
default="REML")
private$..pre_post_cor <- jmvcore::OptionNumber$new(
"pre_post_cor",
pre_post_cor,
min=0,
max=1,
default=0.5)
private$..true_effect <- jmvcore::OptionList$new(
"true_effect",
true_effect,
options=list(
"largest",
"pooled",
"UWLS"),
default="largest")
private$..method.esb <- jmvcore::OptionList$new(
"method.esb",
method.esb,
options=list(
"IT.binom",
"IT.chisq",
"TESS",
"PSST",
"TESSPSST"),
default="TESSPSST")
private$..mult.level <- jmvcore::OptionBool$new(
"mult.level",
mult.level,
default=FALSE)
private$..r <- jmvcore::OptionNumber$new(
"r",
r,
min=0,
max=1,
default=0.8)
private$..n_studies_1 <- jmvcore::OptionString$new(
"n_studies_1",
n_studies_1)
private$..n_studies_2 <- jmvcore::OptionString$new(
"n_studies_2",
n_studies_2)
private$..n_studies_3 <- jmvcore::OptionString$new(
"n_studies_3",
n_studies_3)
private$..n_studies_4 <- jmvcore::OptionString$new(
"n_studies_4",
n_studies_4)
private$..total_n_1 <- jmvcore::OptionString$new(
"total_n_1",
total_n_1)
private$..total_n_2 <- jmvcore::OptionString$new(
"total_n_2",
total_n_2)
private$..total_n_3 <- jmvcore::OptionString$new(
"total_n_3",
total_n_3)
private$..total_n_4 <- jmvcore::OptionString$new(
"total_n_4",
total_n_4)
private$..n_cases_1 <- jmvcore::OptionString$new(
"n_cases_1",
n_cases_1)
private$..n_cases_2 <- jmvcore::OptionString$new(
"n_cases_2",
n_cases_2)
private$..n_cases_3 <- jmvcore::OptionString$new(
"n_cases_3",
n_cases_3)
private$..n_cases_4 <- jmvcore::OptionString$new(
"n_cases_4",
n_cases_4)
private$..p_value_1 <- jmvcore::OptionString$new(
"p_value_1",
p_value_1)
private$..p_value_2 <- jmvcore::OptionString$new(
"p_value_2",
p_value_2)
private$..p_value_3 <- jmvcore::OptionString$new(
"p_value_3",
p_value_3)
private$..p_value_4 <- jmvcore::OptionString$new(
"p_value_4",
p_value_4)
private$..I2_1 <- jmvcore::OptionString$new(
"I2_1",
I2_1)
private$..I2_2 <- jmvcore::OptionString$new(
"I2_2",
I2_2)
private$..I2_3 <- jmvcore::OptionString$new(
"I2_3",
I2_3)
private$..I2_4 <- jmvcore::OptionString$new(
"I2_4",
I2_4)
private$..imprecision_1 <- jmvcore::OptionString$new(
"imprecision_1",
imprecision_1)
private$..imprecision_2 <- jmvcore::OptionString$new(
"imprecision_2",
imprecision_2)
private$..imprecision_3 <- jmvcore::OptionString$new(
"imprecision_3",
imprecision_3)
private$..imprecision_4 <- jmvcore::OptionString$new(
"imprecision_4",
imprecision_4)
private$..rob_1 <- jmvcore::OptionString$new(
"rob_1",
rob_1)
private$..rob_2 <- jmvcore::OptionString$new(
"rob_2",
rob_2)
private$..rob_3 <- jmvcore::OptionString$new(
"rob_3",
rob_3)
private$..rob_4 <- jmvcore::OptionString$new(
"rob_4",
rob_4)
private$..amstar_1 <- jmvcore::OptionString$new(
"amstar_1",
amstar_1)
private$..amstar_2 <- jmvcore::OptionString$new(
"amstar_2",
amstar_2)
private$..amstar_3 <- jmvcore::OptionString$new(
"amstar_3",
amstar_3)
private$..amstar_4 <- jmvcore::OptionString$new(
"amstar_4",
amstar_4)
private$..egger_p_1 <- jmvcore::OptionString$new(
"egger_p_1",
egger_p_1)
private$..egger_p_2 <- jmvcore::OptionString$new(
"egger_p_2",
egger_p_2)
private$..egger_p_3 <- jmvcore::OptionString$new(
"egger_p_3",
egger_p_3)
private$..egger_p_4 <- jmvcore::OptionString$new(
"egger_p_4",
egger_p_4)
private$..esb_p_1 <- jmvcore::OptionString$new(
"esb_p_1",
esb_p_1)
private$..esb_p_2 <- jmvcore::OptionString$new(
"esb_p_2",
esb_p_2)
private$..esb_p_3 <- jmvcore::OptionString$new(
"esb_p_3",
esb_p_3)
private$..esb_p_4 <- jmvcore::OptionString$new(
"esb_p_4",
esb_p_4)
private$..JK_p_1 <- jmvcore::OptionString$new(
"JK_p_1",
JK_p_1)
private$..JK_p_2 <- jmvcore::OptionString$new(
"JK_p_2",
JK_p_2)
private$..JK_p_3 <- jmvcore::OptionString$new(
"JK_p_3",
JK_p_3)
private$..JK_p_4 <- jmvcore::OptionString$new(
"JK_p_4",
JK_p_4)
private$..pi_1 <- jmvcore::OptionBool$new(
"pi_1",
pi_1,
default=FALSE)
private$..pi_2 <- jmvcore::OptionBool$new(
"pi_2",
pi_2,
default=FALSE)
private$..pi_3 <- jmvcore::OptionBool$new(
"pi_3",
pi_3,
default=FALSE)
private$..pi_4 <- jmvcore::OptionBool$new(
"pi_4",
pi_4,
default=FALSE)
private$..largest_CI_1 <- jmvcore::OptionBool$new(
"largest_CI_1",
largest_CI_1,
default=FALSE)
private$..largest_CI_2 <- jmvcore::OptionBool$new(
"largest_CI_2",
largest_CI_2,
default=FALSE)
private$..largest_CI_3 <- jmvcore::OptionBool$new(
"largest_CI_3",
largest_CI_3,
default=FALSE)
private$..largest_CI_4 <- jmvcore::OptionBool$new(
"largest_CI_4",
largest_CI_4,
default=FALSE)
private$..measure_forest <- jmvcore::OptionList$new(
"measure_forest",
measure_forest,
options=list(
"eG",
"eOR"),
default="eG")
private$..class_forest <- jmvcore::OptionList$new(
"class_forest",
class_forest,
options=list(
"no_rest",
"I",
"II",
"III",
"IV",
"High",
"Moderate",
"Weak"),
default="no_rest")
private$..title_forest <- jmvcore::OptionString$new(
"title_forest",
title_forest)
private$..title_xaxis <- jmvcore::OptionString$new(
"title_xaxis",
title_xaxis)
private$..cex <- jmvcore::OptionNumber$new(
"cex",
cex,
min=0,
default=1)
private$..cex_dot <- jmvcore::OptionNumber$new(
"cex_dot",
cex_dot,
min=0,
default=1)
private$..x_lim_adj <- jmvcore::OptionNumber$new(
"x_lim_adj",
x_lim_adj,
default=0)
private$..y_lim_adj <- jmvcore::OptionNumber$new(
"y_lim_adj",
y_lim_adj,
default=0)
private$..max_x <- jmvcore::OptionNumber$new(
"max_x",
max_x,
default=2)
private$..x_axis_adj <- jmvcore::OptionNumber$new(
"x_axis_adj",
x_axis_adj,
default=0)
self$.addOption(private$..vars)
self$.addOption(private$..criteria)
self$.addOption(private$..method.var)
self$.addOption(private$..pre_post_cor)
self$.addOption(private$..true_effect)
self$.addOption(private$..method.esb)
self$.addOption(private$..mult.level)
self$.addOption(private$..r)
self$.addOption(private$..n_studies_1)
self$.addOption(private$..n_studies_2)
self$.addOption(private$..n_studies_3)
self$.addOption(private$..n_studies_4)
self$.addOption(private$..total_n_1)
self$.addOption(private$..total_n_2)
self$.addOption(private$..total_n_3)
self$.addOption(private$..total_n_4)
self$.addOption(private$..n_cases_1)
self$.addOption(private$..n_cases_2)
self$.addOption(private$..n_cases_3)
self$.addOption(private$..n_cases_4)
self$.addOption(private$..p_value_1)
self$.addOption(private$..p_value_2)
self$.addOption(private$..p_value_3)
self$.addOption(private$..p_value_4)
self$.addOption(private$..I2_1)
self$.addOption(private$..I2_2)
self$.addOption(private$..I2_3)
self$.addOption(private$..I2_4)
self$.addOption(private$..imprecision_1)
self$.addOption(private$..imprecision_2)
self$.addOption(private$..imprecision_3)
self$.addOption(private$..imprecision_4)
self$.addOption(private$..rob_1)
self$.addOption(private$..rob_2)
self$.addOption(private$..rob_3)
self$.addOption(private$..rob_4)
self$.addOption(private$..amstar_1)
self$.addOption(private$..amstar_2)
self$.addOption(private$..amstar_3)
self$.addOption(private$..amstar_4)
self$.addOption(private$..egger_p_1)
self$.addOption(private$..egger_p_2)
self$.addOption(private$..egger_p_3)
self$.addOption(private$..egger_p_4)
self$.addOption(private$..esb_p_1)
self$.addOption(private$..esb_p_2)
self$.addOption(private$..esb_p_3)
self$.addOption(private$..esb_p_4)
self$.addOption(private$..JK_p_1)
self$.addOption(private$..JK_p_2)
self$.addOption(private$..JK_p_3)
self$.addOption(private$..JK_p_4)
self$.addOption(private$..pi_1)
self$.addOption(private$..pi_2)
self$.addOption(private$..pi_3)
self$.addOption(private$..pi_4)
self$.addOption(private$..largest_CI_1)
self$.addOption(private$..largest_CI_2)
self$.addOption(private$..largest_CI_3)
self$.addOption(private$..largest_CI_4)
self$.addOption(private$..measure_forest)
self$.addOption(private$..class_forest)
self$.addOption(private$..title_forest)
self$.addOption(private$..title_xaxis)
self$.addOption(private$..cex)
self$.addOption(private$..cex_dot)
self$.addOption(private$..x_lim_adj)
self$.addOption(private$..y_lim_adj)
self$.addOption(private$..max_x)
self$.addOption(private$..x_axis_adj)
}),
active = list(
vars = function() private$..vars$value,
criteria = function() private$..criteria$value,
method.var = function() private$..method.var$value,
pre_post_cor = function() private$..pre_post_cor$value,
true_effect = function() private$..true_effect$value,
method.esb = function() private$..method.esb$value,
mult.level = function() private$..mult.level$value,
r = function() private$..r$value,
n_studies_1 = function() private$..n_studies_1$value,
n_studies_2 = function() private$..n_studies_2$value,
n_studies_3 = function() private$..n_studies_3$value,
n_studies_4 = function() private$..n_studies_4$value,
total_n_1 = function() private$..total_n_1$value,
total_n_2 = function() private$..total_n_2$value,
total_n_3 = function() private$..total_n_3$value,
total_n_4 = function() private$..total_n_4$value,
n_cases_1 = function() private$..n_cases_1$value,
n_cases_2 = function() private$..n_cases_2$value,
n_cases_3 = function() private$..n_cases_3$value,
n_cases_4 = function() private$..n_cases_4$value,
p_value_1 = function() private$..p_value_1$value,
p_value_2 = function() private$..p_value_2$value,
p_value_3 = function() private$..p_value_3$value,
p_value_4 = function() private$..p_value_4$value,
I2_1 = function() private$..I2_1$value,
I2_2 = function() private$..I2_2$value,
I2_3 = function() private$..I2_3$value,
I2_4 = function() private$..I2_4$value,
imprecision_1 = function() private$..imprecision_1$value,
imprecision_2 = function() private$..imprecision_2$value,
imprecision_3 = function() private$..imprecision_3$value,
imprecision_4 = function() private$..imprecision_4$value,
rob_1 = function() private$..rob_1$value,
rob_2 = function() private$..rob_2$value,
rob_3 = function() private$..rob_3$value,
rob_4 = function() private$..rob_4$value,
amstar_1 = function() private$..amstar_1$value,
amstar_2 = function() private$..amstar_2$value,
amstar_3 = function() private$..amstar_3$value,
amstar_4 = function() private$..amstar_4$value,
egger_p_1 = function() private$..egger_p_1$value,
egger_p_2 = function() private$..egger_p_2$value,
egger_p_3 = function() private$..egger_p_3$value,
egger_p_4 = function() private$..egger_p_4$value,
esb_p_1 = function() private$..esb_p_1$value,
esb_p_2 = function() private$..esb_p_2$value,
esb_p_3 = function() private$..esb_p_3$value,
esb_p_4 = function() private$..esb_p_4$value,
JK_p_1 = function() private$..JK_p_1$value,
JK_p_2 = function() private$..JK_p_2$value,
JK_p_3 = function() private$..JK_p_3$value,
JK_p_4 = function() private$..JK_p_4$value,
pi_1 = function() private$..pi_1$value,
pi_2 = function() private$..pi_2$value,
pi_3 = function() private$..pi_3$value,
pi_4 = function() private$..pi_4$value,
largest_CI_1 = function() private$..largest_CI_1$value,
largest_CI_2 = function() private$..largest_CI_2$value,
largest_CI_3 = function() private$..largest_CI_3$value,
largest_CI_4 = function() private$..largest_CI_4$value,
measure_forest = function() private$..measure_forest$value,
class_forest = function() private$..class_forest$value,
title_forest = function() private$..title_forest$value,
title_xaxis = function() private$..title_xaxis$value,
cex = function() private$..cex$value,
cex_dot = function() private$..cex_dot$value,
x_lim_adj = function() private$..x_lim_adj$value,
y_lim_adj = function() private$..y_lim_adj$value,
max_x = function() private$..max_x$value,
x_axis_adj = function() private$..x_axis_adj$value),
private = list(
..vars = NA,
..criteria = NA,
..method.var = NA,
..pre_post_cor = NA,
..true_effect = NA,
..method.esb = NA,
..mult.level = NA,
..r = NA,
..n_studies_1 = NA,
..n_studies_2 = NA,
..n_studies_3 = NA,
..n_studies_4 = NA,
..total_n_1 = NA,
..total_n_2 = NA,
..total_n_3 = NA,
..total_n_4 = NA,
..n_cases_1 = NA,
..n_cases_2 = NA,
..n_cases_3 = NA,
..n_cases_4 = NA,
..p_value_1 = NA,
..p_value_2 = NA,
..p_value_3 = NA,
..p_value_4 = NA,
..I2_1 = NA,
..I2_2 = NA,
..I2_3 = NA,
..I2_4 = NA,
..imprecision_1 = NA,
..imprecision_2 = NA,
..imprecision_3 = NA,
..imprecision_4 = NA,
..rob_1 = NA,
..rob_2 = NA,
..rob_3 = NA,
..rob_4 = NA,
..amstar_1 = NA,
..amstar_2 = NA,
..amstar_3 = NA,
..amstar_4 = NA,
..egger_p_1 = NA,
..egger_p_2 = NA,
..egger_p_3 = NA,
..egger_p_4 = NA,
..esb_p_1 = NA,
..esb_p_2 = NA,
..esb_p_3 = NA,
..esb_p_4 = NA,
..JK_p_1 = NA,
..JK_p_2 = NA,
..JK_p_3 = NA,
..JK_p_4 = NA,
..pi_1 = NA,
..pi_2 = NA,
..pi_3 = NA,
..pi_4 = NA,
..largest_CI_1 = NA,
..largest_CI_2 = NA,
..largest_CI_3 = NA,
..largest_CI_4 = NA,
..measure_forest = NA,
..class_forest = NA,
..title_forest = NA,
..title_xaxis = NA,
..cex = NA,
..cex_dot = NA,
..x_lim_adj = NA,
..y_lim_adj = NA,
..max_x = NA,
..x_axis_adj = NA)
)
umbrellaResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"umbrellaResults",
inherit = jmvcore::Group,
active = list(
text = function() private$.items[["text"]],
checktable = function() private$.items[["checktable"]],
strattable = function() private$.items[["strattable"]],
metatable = function() private$.items[["metatable"]],
addtable = function() private$.items[["addtable"]],
plot = function() private$.items[["plot"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Results of the umbrella review")
self$add(jmvcore::Html$new(
options=options,
name="text"))
self$add(jmvcore::Table$new(
options=options,
name="checktable",
title="List of problematic rows (if any)",
rows=1,
columns=list(
list(
`name`="Row",
`type`="text"),
list(
`name`="Type_errors",
`type`="text"),
list(
`name`="Description_errors",
`type`="text"),
list(
`name`="author",
`type`="text"),
list(
`name`="year",
`type`="text"))))
self$add(jmvcore::Table$new(
options=options,
name="strattable",
title="Summary results",
rows=1,
columns=list(
list(
`name`="Factor",
`type`="text"),
list(
`name`="Criteria",
`type`="text"),
list(
`name`="Class",
`type`="text"),
list(
`name`="n_studies",
`type`="text"),
list(
`name`="total_n",
`type`="text"),
list(
`name`="n_cases",
`type`="text"),
list(
`name`="n_controls",
`type`="text"))))
self$add(jmvcore::Table$new(
options=options,
name="metatable",
title="Core meta-analytic results",
rows=1,
columns=list(
list(
`name`="Factor",
`type`="text"),
list(
`name`="measure",
`type`="text"),
list(
`name`="value",
`type`="text",
`format`="zto"),
list(
`name`="value_CI",
`type`="text",
`format`="zto"),
list(
`name`="eG",
`type`="text",
`format`="zto"),
list(
`name`="eG_CI",
`type`="text",
`format`="zto"),
list(
`name`="eOR",
`type`="text",
`format`="zto"),
list(
`name`="eOR_CI",
`type`="text",
`format`="zto"),
list(
`name`="p_value",
`type`="text",
`format`="zto"))))
self$add(jmvcore::Table$new(
options=options,
name="addtable",
title="Additional results",
rows=1,
columns=list(
list(
`name`="Factor",
`type`="text"),
list(
`name`="I2",
`type`="text",
`format`="zto"),
list(
`name`="PI_eG",
`type`="text",
`format`="zto"),
list(
`name`="PI_eOR",
`type`="text",
`format`="zto"),
list(
`name`="egger_p",
`type`="text",
`format`="zto"),
list(
`name`="ESB_p",
`type`="text",
`format`="zto"),
list(
`name`="power_med",
`type`="text",
`format`="zto"),
list(
`name`="JK_p",
`type`="text",
`format`="zto"),
list(
`name`="largest_CI_eG",
`type`="text",
`format`="zto"),
list(
`name`="largest_CI_eOR",
`type`="text",
`format`="zto"),
list(
`name`="rob",
`type`="text",
`format`="zto"),
list(
`name`="amstar",
`type`="text",
`format`="zto"))))
self$add(jmvcore::Image$new(
options=options,
name="plot",
title="Forest Plot",
width=900,
height=900,
renderFun=".plot"))}))
umbrellaBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"umbrellaBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "metaumbrella",
name = "umbrella",
version = c(1,0,5),
options = options,
results = umbrellaResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE,
requiresMissings = FALSE)
}))
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