Nothing
R/logregord.h.R
In jmv: The 'jamovi' Analyses
Defines functions
logRegOrd
Documented in
logRegOrd
# This file is automatically generated, you probably don't want to edit this
logRegOrdOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"logRegOrdOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
dep = NULL,
covs = NULL,
factors = NULL,
blocks = list(
list()),
refLevels = NULL,
modelTest = FALSE,
dev = TRUE,
aic = TRUE,
bic = FALSE,
pseudoR2 = list(
"r2mf"),
omni = FALSE,
thres = FALSE,
ci = FALSE,
ciWidth = 95,
OR = FALSE,
ciOR = FALSE,
ciWidthOR = 95, ...) {
super$initialize(
package="jmv",
name="logRegOrd",
requiresData=TRUE,
...)
private$..dep <- jmvcore::OptionVariable$new(
"dep",
dep,
suggested=list(
"ordinal"),
permitted=list(
"factor"))
private$..covs <- jmvcore::OptionVariables$new(
"covs",
covs,
suggested=list(
"continuous"),
permitted=list(
"numeric"),
default=NULL)
private$..factors <- jmvcore::OptionVariables$new(
"factors",
factors,
suggested=list(
"nominal"),
permitted=list(
"factor"),
default=NULL)
private$..blocks <- jmvcore::OptionArray$new(
"blocks",
blocks,
default=list(
list()),
template=jmvcore::OptionTerms$new(
"blocks",
NULL))
private$..refLevels <- jmvcore::OptionArray$new(
"refLevels",
refLevels,
items="(factors)",
default=NULL,
template=jmvcore::OptionGroup$new(
"refLevels",
NULL,
elements=list(
jmvcore::OptionVariable$new(
"var",
NULL,
content="$key"),
jmvcore::OptionLevel$new(
"ref",
NULL))))
private$..modelTest <- jmvcore::OptionBool$new(
"modelTest",
modelTest,
default=FALSE)
private$..dev <- jmvcore::OptionBool$new(
"dev",
dev,
default=TRUE)
private$..aic <- jmvcore::OptionBool$new(
"aic",
aic,
default=TRUE)
private$..bic <- jmvcore::OptionBool$new(
"bic",
bic,
default=FALSE)
private$..pseudoR2 <- jmvcore::OptionNMXList$new(
"pseudoR2",
pseudoR2,
options=list(
"r2mf",
"r2cs",
"r2n"),
default=list(
"r2mf"))
private$..omni <- jmvcore::OptionBool$new(
"omni",
omni,
default=FALSE)
private$..thres <- jmvcore::OptionBool$new(
"thres",
thres,
default=FALSE)
private$..ci <- jmvcore::OptionBool$new(
"ci",
ci,
default=FALSE)
private$..ciWidth <- jmvcore::OptionNumber$new(
"ciWidth",
ciWidth,
min=50,
max=99.9,
default=95)
private$..OR <- jmvcore::OptionBool$new(
"OR",
OR,
default=FALSE)
private$..ciOR <- jmvcore::OptionBool$new(
"ciOR",
ciOR,
default=FALSE)
private$..ciWidthOR <- jmvcore::OptionNumber$new(
"ciWidthOR",
ciWidthOR,
min=50,
max=99.9,
default=95)
self$.addOption(private$..dep)
self$.addOption(private$..covs)
self$.addOption(private$..factors)
self$.addOption(private$..blocks)
self$.addOption(private$..refLevels)
self$.addOption(private$..modelTest)
self$.addOption(private$..dev)
self$.addOption(private$..aic)
self$.addOption(private$..bic)
self$.addOption(private$..pseudoR2)
self$.addOption(private$..omni)
self$.addOption(private$..thres)
self$.addOption(private$..ci)
self$.addOption(private$..ciWidth)
self$.addOption(private$..OR)
self$.addOption(private$..ciOR)
self$.addOption(private$..ciWidthOR)
}),
active = list(
dep = function() private$..dep$value,
covs = function() private$..covs$value,
factors = function() private$..factors$value,
blocks = function() private$..blocks$value,
refLevels = function() private$..refLevels$value,
modelTest = function() private$..modelTest$value,
dev = function() private$..dev$value,
aic = function() private$..aic$value,
bic = function() private$..bic$value,
pseudoR2 = function() private$..pseudoR2$value,
omni = function() private$..omni$value,
thres = function() private$..thres$value,
ci = function() private$..ci$value,
ciWidth = function() private$..ciWidth$value,
OR = function() private$..OR$value,
ciOR = function() private$..ciOR$value,
ciWidthOR = function() private$..ciWidthOR$value),
private = list(
..dep = NA,
..covs = NA,
..factors = NA,
..blocks = NA,
..refLevels = NA,
..modelTest = NA,
..dev = NA,
..aic = NA,
..bic = NA,
..pseudoR2 = NA,
..omni = NA,
..thres = NA,
..ci = NA,
..ciWidth = NA,
..OR = NA,
..ciOR = NA,
..ciWidthOR = NA)
)
logRegOrdResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"logRegOrdResults",
inherit = jmvcore::Group,
active = list(
modelFit = function() private$.items[["modelFit"]],
modelComp = function() private$.items[["modelComp"]],
models = function() private$.items[["models"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Ordinal Logistic Regression")
self$add(jmvcore::Table$new(
options=options,
name="modelFit",
title="Model Fit Measures",
clearWith=list(
"dep",
"blocks"),
visible="(dev || aic || bic || pseudoR2:r2mf || pseudoR2:r2cs || pseudoR2:r2n || modelTest)",
columns=list(
list(
`name`="model",
`title`="Model",
`type`="text"),
list(
`name`="dev",
`title`="Deviance",
`type`="number",
`visible`="(dev)"),
list(
`name`="aic",
`title`="AIC",
`type`="number",
`visible`="(aic)"),
list(
`name`="bic",
`title`="BIC",
`type`="number",
`visible`="(bic)"),
list(
`name`="r2mf",
`title`="R\u00B2<sub>McF</sub>",
`type`="number",
`visible`="(pseudoR2:r2mf)"),
list(
`name`="r2cs",
`title`="R\u00B2<sub>CS</sub>",
`type`="number",
`visible`="(pseudoR2:r2cs)"),
list(
`name`="r2n",
`title`="R\u00B2<sub>N</sub>",
`type`="number",
`visible`="(pseudoR2:r2n)"),
list(
`name`="chi",
`title`="\u03C7\u00B2",
`type`="number",
`superTitle`="Overall Model Test",
`visible`="(modelTest)"),
list(
`name`="df",
`title`="df",
`type`="integer",
`superTitle`="Overall Model Test",
`visible`="(modelTest)"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`superTitle`="Overall Model Test",
`visible`="(modelTest)"))))
self$add(jmvcore::Table$new(
options=options,
name="modelComp",
title="Model Comparisons",
clearWith=list(
"dep",
"blocks"),
columns=list(
list(
`name`="model1",
`title`="Model",
`content`=".",
`type`="text",
`superTitle`="Comparison"),
list(
`name`="sep",
`title`="",
`content`="-",
`type`="text",
`format`="narrow",
`superTitle`="Comparison"),
list(
`name`="model2",
`title`="Model",
`content`=".",
`type`="text",
`superTitle`="Comparison"),
list(
`name`="chi",
`title`="\u03C7\u00B2",
`type`="number"),
list(
`name`="df",
`title`="df",
`type`="integer"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Array$new(
options=options,
name="models",
title="Model Specific Results",
layout="listSelect",
hideHeadingOnlyChild=TRUE,
template=R6::R6Class(
inherit = jmvcore::Group,
active = list(
lrt = function() private$.items[["lrt"]],
coef = function() private$.items[["coef"]],
thres = function() private$.items[["thres"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="undefined",
title="")
self$add(jmvcore::Table$new(
options=options,
name="lrt",
title="Omnibus Likelihood Ratio Tests",
clearWith=list(
"dep",
"blocks"),
visible="(omni)",
refs="car",
columns=list(
list(
`name`="term",
`title`="Predictor",
`type`="text"),
list(
`name`="chi",
`title`="\u03C7\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="coef",
title="`Model Coefficients - ${dep}`",
clearWith=list(
"dep",
"blocks",
"refLevels"),
refs="MASS",
columns=list(
list(
`name`="term",
`title`="Predictor",
`type`="text"),
list(
`name`="est",
`title`="Estimate",
`type`="number"),
list(
`name`="lower",
`title`="Lower",
`type`="number",
`visible`="(ci)"),
list(
`name`="upper",
`title`="Upper",
`type`="number",
`visible`="(ci)"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="z",
`title`="Z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"),
list(
`name`="odds",
`title`="Odds ratio",
`type`="number",
`visible`="(OR)"),
list(
`name`="oddsLower",
`title`="Lower",
`type`="number",
`visible`="(ciOR && OR)"),
list(
`name`="oddsUpper",
`title`="Upper",
`type`="number",
`visible`="(ciOR && OR)"))))
self$add(jmvcore::Table$new(
options=options,
name="thres",
title="Model Thresholds",
clearWith=list(
"dep",
"blocks",
"refLevels"),
visible="(thres)",
columns=list(
list(
`name`="term",
`title`="Threshold",
`type`="text"),
list(
`name`="est",
`title`="Estimate",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="z",
`title`="Z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"),
list(
`name`="odds",
`title`="Odds ratio",
`type`="number",
`visible`="(OR)"))))}))$new(options=options)))}))
logRegOrdBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"logRegOrdBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "jmv",
name = "logRegOrd",
version = c(1,0,0),
options = options,
results = logRegOrdResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE,
requiresMissings = FALSE,
weightsSupport = 'integerOnly')
}))
#' Ordinal Logistic Regression
#'
#' Ordinal Logistic Regression
#'
#' @examples
#' set.seed(1337)
#'
#' y <- factor(sample(1:3, 100, replace = TRUE))
#' x1 <- rnorm(100)
#' x2 <- rnorm(100)
#'
#' df <- data.frame(y=y, x1=x1, x2=x2)
#'
#' logRegOrd(data = df, dep = y,
#' covs = vars(x1, x2),
#' blocks = list(list("x1", "x2")))
#'
#' #
#' # ORDINAL LOGISTIC REGRESSION
#' #
#' # Model Fit Measures
#' # ---------------------------------------
#' # Model Deviance AIC R²-McF
#' # ---------------------------------------
#' # 1 218 226 5.68e-4
#' # ---------------------------------------
#' #
#' #
#' # MODEL SPECIFIC RESULTS
#' #
#' # MODEL 1
#' #
#' # Model Coefficients
#' # ----------------------------------------------------
#' # Predictor Estimate SE Z p
#' # ----------------------------------------------------
#' # x1 0.0579 0.193 0.300 0.764
#' # x2 0.0330 0.172 0.192 0.848
#' # ----------------------------------------------------
#' #
#' #
#'
#' @param data the data as a data frame
#' @param dep a string naming the dependent variable from \code{data},
#' variable must be a factor
#' @param covs a vector of strings naming the covariates from \code{data}
#' @param factors a vector of strings naming the fixed factors from
#' \code{data}
#' @param blocks a list containing vectors of strings that name the predictors
#' that are added to the model. The elements are added to the model according
#' to their order in the list
#' @param refLevels a list of lists specifying reference levels of the
#' dependent variable and all the factors
#' @param modelTest \code{TRUE} or \code{FALSE} (default), provide the model
#' comparison between the models and the NULL model
#' @param dev \code{TRUE} (default) or \code{FALSE}, provide the deviance (or
#' -2LogLikelihood) for the models
#' @param aic \code{TRUE} (default) or \code{FALSE}, provide Aikaike's
#' Information Criterion (AIC) for the models
#' @param bic \code{TRUE} or \code{FALSE} (default), provide Bayesian
#' Information Criterion (BIC) for the models
#' @param pseudoR2 one or more of \code{'r2mf'}, \code{'r2cs'}, or
#' \code{'r2n'}; use McFadden's, Cox & Snell, and Nagelkerke pseudo-R²,
#' respectively
#' @param omni \code{TRUE} or \code{FALSE} (default), provide the omnibus
#' likelihood ratio tests for the predictors
#' @param thres \code{TRUE} or \code{FALSE} (default), provide the thresholds
#' that are used as cut-off scores for the levels of the dependent variable
#' @param ci \code{TRUE} or \code{FALSE} (default), provide a confidence
#' interval for the model coefficient estimates
#' @param ciWidth a number between 50 and 99.9 (default: 95) specifying the
#' confidence interval width
#' @param OR \code{TRUE} or \code{FALSE} (default), provide the exponential of
#' the log-odds ratio estimate, or the odds ratio estimate
#' @param ciOR \code{TRUE} or \code{FALSE} (default), provide a confidence
#' interval for the model coefficient odds ratio estimates
#' @param ciWidthOR a number between 50 and 99.9 (default: 95) specifying the
#' confidence interval width
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$modelFit} \tab \tab \tab \tab \tab a table \cr
#' \code{results$modelComp} \tab \tab \tab \tab \tab a table \cr
#' \code{results$models} \tab \tab \tab \tab \tab an array of model specific results \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$modelFit$asDF}
#'
#' \code{as.data.frame(results$modelFit)}
#'
#' @export
logRegOrd <- function(
data,
dep,
covs = NULL,
factors = NULL,
blocks = list(
list()),
refLevels = NULL,
modelTest = FALSE,
dev = TRUE,
aic = TRUE,
bic = FALSE,
pseudoR2 = list(
"r2mf"),
omni = FALSE,
thres = FALSE,
ci = FALSE,
ciWidth = 95,
OR = FALSE,
ciOR = FALSE,
ciWidthOR = 95) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("logRegOrd requires jmvcore to be installed (restart may be required)")
if ( ! missing(dep)) dep <- jmvcore::resolveQuo(jmvcore::enquo(dep))
if ( ! missing(covs)) covs <- jmvcore::resolveQuo(jmvcore::enquo(covs))
if ( ! missing(factors)) factors <- jmvcore::resolveQuo(jmvcore::enquo(factors))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(dep), dep, NULL),
`if`( ! missing(covs), covs, NULL),
`if`( ! missing(factors), factors, NULL))
for (v in dep) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
for (v in factors) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- logRegOrdOptions$new(
dep = dep,
covs = covs,
factors = factors,
blocks = blocks,
refLevels = refLevels,
modelTest = modelTest,
dev = dev,
aic = aic,
bic = bic,
pseudoR2 = pseudoR2,
omni = omni,
thres = thres,
ci = ci,
ciWidth = ciWidth,
OR = OR,
ciOR = ciOR,
ciWidthOR = ciWidthOR)
analysis <- logRegOrdClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
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Defines functions logRegOrd
Documented in logRegOrd
# This file is automatically generated, you probably don't want to edit this
logRegOrdOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"logRegOrdOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
dep = NULL,
covs = NULL,
factors = NULL,
blocks = list(
list()),
refLevels = NULL,
modelTest = FALSE,
dev = TRUE,
aic = TRUE,
bic = FALSE,
pseudoR2 = list(
"r2mf"),
omni = FALSE,
thres = FALSE,
ci = FALSE,
ciWidth = 95,
OR = FALSE,
ciOR = FALSE,
ciWidthOR = 95, ...) {
super$initialize(
package="jmv",
name="logRegOrd",
requiresData=TRUE,
...)
private$..dep <- jmvcore::OptionVariable$new(
"dep",
dep,
suggested=list(
"ordinal"),
permitted=list(
"factor"))
private$..covs <- jmvcore::OptionVariables$new(
"covs",
covs,
suggested=list(
"continuous"),
permitted=list(
"numeric"),
default=NULL)
private$..factors <- jmvcore::OptionVariables$new(
"factors",
factors,
suggested=list(
"nominal"),
permitted=list(
"factor"),
default=NULL)
private$..blocks <- jmvcore::OptionArray$new(
"blocks",
blocks,
default=list(
list()),
template=jmvcore::OptionTerms$new(
"blocks",
NULL))
private$..refLevels <- jmvcore::OptionArray$new(
"refLevels",
refLevels,
items="(factors)",
default=NULL,
template=jmvcore::OptionGroup$new(
"refLevels",
NULL,
elements=list(
jmvcore::OptionVariable$new(
"var",
NULL,
content="$key"),
jmvcore::OptionLevel$new(
"ref",
NULL))))
private$..modelTest <- jmvcore::OptionBool$new(
"modelTest",
modelTest,
default=FALSE)
private$..dev <- jmvcore::OptionBool$new(
"dev",
dev,
default=TRUE)
private$..aic <- jmvcore::OptionBool$new(
"aic",
aic,
default=TRUE)
private$..bic <- jmvcore::OptionBool$new(
"bic",
bic,
default=FALSE)
private$..pseudoR2 <- jmvcore::OptionNMXList$new(
"pseudoR2",
pseudoR2,
options=list(
"r2mf",
"r2cs",
"r2n"),
default=list(
"r2mf"))
private$..omni <- jmvcore::OptionBool$new(
"omni",
omni,
default=FALSE)
private$..thres <- jmvcore::OptionBool$new(
"thres",
thres,
default=FALSE)
private$..ci <- jmvcore::OptionBool$new(
"ci",
ci,
default=FALSE)
private$..ciWidth <- jmvcore::OptionNumber$new(
"ciWidth",
ciWidth,
min=50,
max=99.9,
default=95)
private$..OR <- jmvcore::OptionBool$new(
"OR",
OR,
default=FALSE)
private$..ciOR <- jmvcore::OptionBool$new(
"ciOR",
ciOR,
default=FALSE)
private$..ciWidthOR <- jmvcore::OptionNumber$new(
"ciWidthOR",
ciWidthOR,
min=50,
max=99.9,
default=95)
self$.addOption(private$..dep)
self$.addOption(private$..covs)
self$.addOption(private$..factors)
self$.addOption(private$..blocks)
self$.addOption(private$..refLevels)
self$.addOption(private$..modelTest)
self$.addOption(private$..dev)
self$.addOption(private$..aic)
self$.addOption(private$..bic)
self$.addOption(private$..pseudoR2)
self$.addOption(private$..omni)
self$.addOption(private$..thres)
self$.addOption(private$..ci)
self$.addOption(private$..ciWidth)
self$.addOption(private$..OR)
self$.addOption(private$..ciOR)
self$.addOption(private$..ciWidthOR)
}),
active = list(
dep = function() private$..dep$value,
covs = function() private$..covs$value,
factors = function() private$..factors$value,
blocks = function() private$..blocks$value,
refLevels = function() private$..refLevels$value,
modelTest = function() private$..modelTest$value,
dev = function() private$..dev$value,
aic = function() private$..aic$value,
bic = function() private$..bic$value,
pseudoR2 = function() private$..pseudoR2$value,
omni = function() private$..omni$value,
thres = function() private$..thres$value,
ci = function() private$..ci$value,
ciWidth = function() private$..ciWidth$value,
OR = function() private$..OR$value,
ciOR = function() private$..ciOR$value,
ciWidthOR = function() private$..ciWidthOR$value),
private = list(
..dep = NA,
..covs = NA,
..factors = NA,
..blocks = NA,
..refLevels = NA,
..modelTest = NA,
..dev = NA,
..aic = NA,
..bic = NA,
..pseudoR2 = NA,
..omni = NA,
..thres = NA,
..ci = NA,
..ciWidth = NA,
..OR = NA,
..ciOR = NA,
..ciWidthOR = NA)
)
logRegOrdResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"logRegOrdResults",
inherit = jmvcore::Group,
active = list(
modelFit = function() private$.items[["modelFit"]],
modelComp = function() private$.items[["modelComp"]],
models = function() private$.items[["models"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Ordinal Logistic Regression")
self$add(jmvcore::Table$new(
options=options,
name="modelFit",
title="Model Fit Measures",
clearWith=list(
"dep",
"blocks"),
visible="(dev || aic || bic || pseudoR2:r2mf || pseudoR2:r2cs || pseudoR2:r2n || modelTest)",
columns=list(
list(
`name`="model",
`title`="Model",
`type`="text"),
list(
`name`="dev",
`title`="Deviance",
`type`="number",
`visible`="(dev)"),
list(
`name`="aic",
`title`="AIC",
`type`="number",
`visible`="(aic)"),
list(
`name`="bic",
`title`="BIC",
`type`="number",
`visible`="(bic)"),
list(
`name`="r2mf",
`title`="R\u00B2<sub>McF</sub>",
`type`="number",
`visible`="(pseudoR2:r2mf)"),
list(
`name`="r2cs",
`title`="R\u00B2<sub>CS</sub>",
`type`="number",
`visible`="(pseudoR2:r2cs)"),
list(
`name`="r2n",
`title`="R\u00B2<sub>N</sub>",
`type`="number",
`visible`="(pseudoR2:r2n)"),
list(
`name`="chi",
`title`="\u03C7\u00B2",
`type`="number",
`superTitle`="Overall Model Test",
`visible`="(modelTest)"),
list(
`name`="df",
`title`="df",
`type`="integer",
`superTitle`="Overall Model Test",
`visible`="(modelTest)"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`superTitle`="Overall Model Test",
`visible`="(modelTest)"))))
self$add(jmvcore::Table$new(
options=options,
name="modelComp",
title="Model Comparisons",
clearWith=list(
"dep",
"blocks"),
columns=list(
list(
`name`="model1",
`title`="Model",
`content`=".",
`type`="text",
`superTitle`="Comparison"),
list(
`name`="sep",
`title`="",
`content`="-",
`type`="text",
`format`="narrow",
`superTitle`="Comparison"),
list(
`name`="model2",
`title`="Model",
`content`=".",
`type`="text",
`superTitle`="Comparison"),
list(
`name`="chi",
`title`="\u03C7\u00B2",
`type`="number"),
list(
`name`="df",
`title`="df",
`type`="integer"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Array$new(
options=options,
name="models",
title="Model Specific Results",
layout="listSelect",
hideHeadingOnlyChild=TRUE,
template=R6::R6Class(
inherit = jmvcore::Group,
active = list(
lrt = function() private$.items[["lrt"]],
coef = function() private$.items[["coef"]],
thres = function() private$.items[["thres"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="undefined",
title="")
self$add(jmvcore::Table$new(
options=options,
name="lrt",
title="Omnibus Likelihood Ratio Tests",
clearWith=list(
"dep",
"blocks"),
visible="(omni)",
refs="car",
columns=list(
list(
`name`="term",
`title`="Predictor",
`type`="text"),
list(
`name`="chi",
`title`="\u03C7\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="coef",
title="`Model Coefficients - ${dep}`",
clearWith=list(
"dep",
"blocks",
"refLevels"),
refs="MASS",
columns=list(
list(
`name`="term",
`title`="Predictor",
`type`="text"),
list(
`name`="est",
`title`="Estimate",
`type`="number"),
list(
`name`="lower",
`title`="Lower",
`type`="number",
`visible`="(ci)"),
list(
`name`="upper",
`title`="Upper",
`type`="number",
`visible`="(ci)"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="z",
`title`="Z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"),
list(
`name`="odds",
`title`="Odds ratio",
`type`="number",
`visible`="(OR)"),
list(
`name`="oddsLower",
`title`="Lower",
`type`="number",
`visible`="(ciOR && OR)"),
list(
`name`="oddsUpper",
`title`="Upper",
`type`="number",
`visible`="(ciOR && OR)"))))
self$add(jmvcore::Table$new(
options=options,
name="thres",
title="Model Thresholds",
clearWith=list(
"dep",
"blocks",
"refLevels"),
visible="(thres)",
columns=list(
list(
`name`="term",
`title`="Threshold",
`type`="text"),
list(
`name`="est",
`title`="Estimate",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"),
list(
`name`="z",
`title`="Z",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"),
list(
`name`="odds",
`title`="Odds ratio",
`type`="number",
`visible`="(OR)"))))}))$new(options=options)))}))
logRegOrdBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"logRegOrdBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "jmv",
name = "logRegOrd",
version = c(1,0,0),
options = options,
results = logRegOrdResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE,
requiresMissings = FALSE,
weightsSupport = 'integerOnly')
}))
#' Ordinal Logistic Regression
#'
#' Ordinal Logistic Regression
#'
#' @examples
#' set.seed(1337)
#'
#' y <- factor(sample(1:3, 100, replace = TRUE))
#' x1 <- rnorm(100)
#' x2 <- rnorm(100)
#'
#' df <- data.frame(y=y, x1=x1, x2=x2)
#'
#' logRegOrd(data = df, dep = y,
#' covs = vars(x1, x2),
#' blocks = list(list("x1", "x2")))
#'
#' #
#' # ORDINAL LOGISTIC REGRESSION
#' #
#' # Model Fit Measures
#' # ---------------------------------------
#' # Model Deviance AIC R²-McF
#' # ---------------------------------------
#' # 1 218 226 5.68e-4
#' # ---------------------------------------
#' #
#' #
#' # MODEL SPECIFIC RESULTS
#' #
#' # MODEL 1
#' #
#' # Model Coefficients
#' # ----------------------------------------------------
#' # Predictor Estimate SE Z p
#' # ----------------------------------------------------
#' # x1 0.0579 0.193 0.300 0.764
#' # x2 0.0330 0.172 0.192 0.848
#' # ----------------------------------------------------
#' #
#' #
#'
#' @param data the data as a data frame
#' @param dep a string naming the dependent variable from \code{data},
#' variable must be a factor
#' @param covs a vector of strings naming the covariates from \code{data}
#' @param factors a vector of strings naming the fixed factors from
#' \code{data}
#' @param blocks a list containing vectors of strings that name the predictors
#' that are added to the model. The elements are added to the model according
#' to their order in the list
#' @param refLevels a list of lists specifying reference levels of the
#' dependent variable and all the factors
#' @param modelTest \code{TRUE} or \code{FALSE} (default), provide the model
#' comparison between the models and the NULL model
#' @param dev \code{TRUE} (default) or \code{FALSE}, provide the deviance (or
#' -2LogLikelihood) for the models
#' @param aic \code{TRUE} (default) or \code{FALSE}, provide Aikaike's
#' Information Criterion (AIC) for the models
#' @param bic \code{TRUE} or \code{FALSE} (default), provide Bayesian
#' Information Criterion (BIC) for the models
#' @param pseudoR2 one or more of \code{'r2mf'}, \code{'r2cs'}, or
#' \code{'r2n'}; use McFadden's, Cox & Snell, and Nagelkerke pseudo-R²,
#' respectively
#' @param omni \code{TRUE} or \code{FALSE} (default), provide the omnibus
#' likelihood ratio tests for the predictors
#' @param thres \code{TRUE} or \code{FALSE} (default), provide the thresholds
#' that are used as cut-off scores for the levels of the dependent variable
#' @param ci \code{TRUE} or \code{FALSE} (default), provide a confidence
#' interval for the model coefficient estimates
#' @param ciWidth a number between 50 and 99.9 (default: 95) specifying the
#' confidence interval width
#' @param OR \code{TRUE} or \code{FALSE} (default), provide the exponential of
#' the log-odds ratio estimate, or the odds ratio estimate
#' @param ciOR \code{TRUE} or \code{FALSE} (default), provide a confidence
#' interval for the model coefficient odds ratio estimates
#' @param ciWidthOR a number between 50 and 99.9 (default: 95) specifying the
#' confidence interval width
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$modelFit} \tab \tab \tab \tab \tab a table \cr
#' \code{results$modelComp} \tab \tab \tab \tab \tab a table \cr
#' \code{results$models} \tab \tab \tab \tab \tab an array of model specific results \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$modelFit$asDF}
#'
#' \code{as.data.frame(results$modelFit)}
#'
#' @export
logRegOrd <- function(
data,
dep,
covs = NULL,
factors = NULL,
blocks = list(
list()),
refLevels = NULL,
modelTest = FALSE,
dev = TRUE,
aic = TRUE,
bic = FALSE,
pseudoR2 = list(
"r2mf"),
omni = FALSE,
thres = FALSE,
ci = FALSE,
ciWidth = 95,
OR = FALSE,
ciOR = FALSE,
ciWidthOR = 95) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("logRegOrd requires jmvcore to be installed (restart may be required)")
if ( ! missing(dep)) dep <- jmvcore::resolveQuo(jmvcore::enquo(dep))
if ( ! missing(covs)) covs <- jmvcore::resolveQuo(jmvcore::enquo(covs))
if ( ! missing(factors)) factors <- jmvcore::resolveQuo(jmvcore::enquo(factors))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(dep), dep, NULL),
`if`( ! missing(covs), covs, NULL),
`if`( ! missing(factors), factors, NULL))
for (v in dep) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
for (v in factors) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- logRegOrdOptions$new(
dep = dep,
covs = covs,
factors = factors,
blocks = blocks,
refLevels = refLevels,
modelTest = modelTest,
dev = dev,
aic = aic,
bic = bic,
pseudoR2 = pseudoR2,
omni = omni,
thres = thres,
ci = ci,
ciWidth = ciWidth,
OR = OR,
ciOR = ciOR,
ciWidthOR = ciWidthOR)
analysis <- logRegOrdClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
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