much more documentation updates

R/pj_estimate.R

@@ -7,29 +7,29 @@
 #' @import estimatr
 #' @importFrom MASS mvrnorm
 #' @keywords internal
-#' @param .data A `projoint_data` object
-#' @param .structure Either "profile_level" (default) or "choice_level" 
-#' @param .estimand Either "mm" for marginal mean or "amce" for average marginal component effect
-#' @param .att_choose A character column name identifying the attribute of interest (i.e., for the attribute-level or attribute-levels *chosen*).
-#' @param .lev_choose  A character vector identifying the level or levels of interest (i.e., for the attribute-level or attribute-levels *chosen*). Its length should be 1 for profile-level analysis and 1+ for choice-level analysis
-#' @param .att_notchoose A character column name identifying the attribute of interest (i.e., for the attribute-level or attribute-levels *not chosen*). This argument should be specified only if the `.structure` argument is "choice-level".
-#' @param .lev_notchoose  A character vector identifying the level or levels of interest (i.e., for the attribute-level or attribute-levels *not chosen*). Its length should be 1 for profile-level analysis and 1+ for choice-level analysis. This argument should be specified only if the `.structure` argument is "choice-level".
-#' @param .att_choose_b [baseline for AMCE] A character column name identifying the attribute of interest (i.e., for the attribute-level or attribute-levels *chosen*).
-#' @param .lev_choose_b  [baseline for AMCE] A character vector identifying the level or levels of interest (i.e., for the attribute-level or attribute-levels *chosen*). Its length should be 1 for profile-level analysis and 1+ for choice-level analysis
-#' @param .att_notchoose_b [baseline for AMCE] A character column name identifying the attribute of interest (i.e., for the attribute-level or attribute-levels *not chosen*). This argument should be specified only if the `.structure` argument is "choice-level".
-#' @param .lev_notchoose_b [baseline for AMCE]  A character vector identifying the level or levels of interest (i.e., for the attribute-level or attribute-levels *not chosen*). Its length should be 1 for profile-level analysis and 1+ for choice-level analysis. This argument should be specified only if the `.structure` argument is "choice-level".
-#' @param .se_method c("analytic", "simulation", "bootstrap") description
-#' @param .irr NULL (default) if IRR is to be calculated using the repeated task. Otherwise, a numerical value
-#' @param .remove_ties Logical: should ties be removed before estimation? Defaults to TRUE.
-#' @param .ignore_position TRUE (default) if you ignore the location of profile (left or right. Relevant only if analyzed at the choice level
-#' @param .n_sims The number of simulations. Relevant only if .se_method == "simulation" 
-#' @param .n_boot The number of bootstrapped samples. Relevant only if .se_method == "bootstrap"
-#' @param .weights_1 the weight to estimate IRR (see `lm_robust()`): NULL (default)
-#' @param .clusters_1 the clusters to estimate IRR (see `lm_robust()`): NULL (default)
-#' @param .se_type_1 the standard error type to estimate IRR (see `lm_robust()`): "classical" (default)
-#' @param .weights_2 the weight to estimate MM or AMCE (see `lm_robust()`): NULL (default)
-#' @param .clusters_2 the clusters to estimate MM or AMCE (see `lm_robust()`): NULL (default)
-#' @param .se_type_2 the standard error type to estimate MM or AMCE (see `lm_robust()`): "classical" (default)
+#' @param .data A \code{\link{projoint_data}} object
+#' @param .structure Either \code{"profile_level"} (default) or \code{"choice_level"} 
+#' @param .estimand Either \code{"mm"} for marginal mean or \code{"amce"} for average marginal component effect
+#' @param .att_choose A character column name identifying the attribute of interest (i.e., for the attribute-level or attribute-levels \strong{chosen}).
+#' @param .lev_choose  A character vector identifying the level or levels of interest (i.e., for the attribute-level or attribute-levels \strong{chosen}). Its length should be 1 for profile-level analysis and 1+ for choice-level analysis
+#' @param .att_notchoose A character column name identifying the attribute of interest (i.e., for the attribute-level or attribute-levels \strong{not chosen}). This argument should be specified only if the \code{.structure} argument is \code{"choice-level"}.
+#' @param .lev_notchoose  A character vector identifying the level or levels of interest (i.e., for the attribute-level or attribute-levels \strong{not chosen}). Its length should be 1 for profile-level analysis and 1+ for choice-level analysis. This argument should be specified only if the \code{.structure} argument is \code{"choice-level"}.
+#' @param .att_choose_b [baseline for AMCE] A character column name identifying the attribute of interest (i.e., for the attribute-level or attribute-levels \strong{chosen}).
+#' @param .lev_choose_b  [baseline for AMCE] A character vector identifying the level or levels of interest (i.e., for the attribute-level or attribute-levels \strong{chosen}). Its length should be 1 for profile-level analysis and 1+ for choice-level analysis
+#' @param .att_notchoose_b [baseline for AMCE] A character column name identifying the attribute of interest (i.e., for the attribute-level or attribute-levels \strong{not chosen*}). This argument should be specified only if the \code{.structure} argument is \code{"choice-level"}.
+#' @param .lev_notchoose_b [baseline for AMCE]  A character vector identifying the level or levels of interest (i.e., for the attribute-level or attribute-levels \strong{not chosen}). Its length should be 1 for profile-level analysis and 1+ for choice-level analysis. This argument should be specified only if the \code{.structure} argument is \code{"choice-level"}.
+#' @param .se_method By default, \code{c("analytic", "simulation", "bootstrap")} description
+#' @param .irr \code{NULL} (default) if IRR is to be calculated using the repeated task. Otherwise, a numerical value
+#' @param .remove_ties Logical: should ties be removed before estimation? Defaults to \code{TRUE}.
+#' @param .ignore_position \code{TRUE} (default) if you ignore the location of profile (left or right). Relevant only if analyzed at the choice level
+#' @param .n_sims The number of simulations. Relevant only if \code{.se_method == "simulation"} 
+#' @param .n_boot The number of bootstrapped samples. Relevant only if \code{.se_method == "bootstrap"}
+#' @param .weights_1 the weight to estimate IRR (see \code{\link[estimatr]{lm_robust}}): \code{NULL} (default)
+#' @param .clusters_1 the clusters to estimate IRR (see \code{\link[estimatr]{lm_robust}}): \code{NULL} (default)
+#' @param .se_type_1 the standard error type to estimate IRR (see \code{\link[estimatr]{lm_robust}}): \code{"classical"} (default)
+#' @param .weights_2 the weight to estimate MM or AMCE (see \code{\link[estimatr]{lm_robust}}): \code{NULL} (default)
+#' @param .clusters_2 the clusters to estimate MM or AMCE (see \code{\link[estimatr]{lm_robust}}): \code{NULL} (default)
+#' @param .se_type_2 the standard error type to estimate MM or AMCE (see \code{\link[estimatr]{lm_robust}}): \code{"classical"} (default)
 #' @return A data frame of estimates
 
 # .data <- df

R/plot.projoint_results.R

@@ -1,19 +1,19 @@
 #' Plot all MMs or AMCEs
 #'
-#' This method produces MM or AMCE plots given a \code\link{projoint_results} object, the output from the \code\link{projoint} function.
+#' This method produces MM or AMCE plots given a \code{\link{projoint_results}} object, the output from the \code{\link{projoint}} function.
 #'
 #' @import ggplot2
 #' @import ggthemes
 #' @import dplyr
 #' @import stringr
-#' @param x A \code\link{projoint_results} object
+#' @param x A \code{\link{projoint_results}} object
 #' @param .estimand Either \code{"mm"} for marginal mean (default) or \code{"amce"} for average marginal component effect
 #' @param .estimates The estimates to be plotted, either \code{"corrected"} (default), \code{"uncorrected"}, or \code{"both"}
 #' @param .by_var \code{TRUE} to plot the difference in estimates between the two subgroups, \code{FALSE} (default) otherwise 
 #' @param .base_size base font size, given in pts.
 #' @param .base_family base font family
 #' @param ... Additional optional arguments
-#' @return A ggplot object
+#' @return A \code{ggplot} object
 #' @export
 #' @examples
 #' 

R/predict_tau.R

@@ -278,7 +278,7 @@ predict_tau <- function(
 
 
 
-#' @param x An object of class `projoint_tau` derived from `predict_tau`
+#' @param x An object of class \code{\link{projoint_tau}} derived from \code{\link{predict_tau}}
 #' @param ... Optional arguments; currently none accepted
 #' @export
 #' @rdname predict_tau
@@ -291,17 +291,17 @@ print.projoint_tau <- function(x, ...) {
    # No results
 }
 
-#' @param object An object of class `projoint_tau` derived from `predict_tau`
+#' @param object An object of class \code{\link{projoint_tau}} derived from \code{\link{predict_tau}}
 #' @param ... Optional arguments; currently none accepted
 #' @export
-#' @return A tibble showing IRR as profile similarity changes. The value of `predicted` when `x=0` is the estimated IRR.
+#' @return A tibble showing IRR as profile similarity changes. The value of \code{predicted} when \code{x=0} is the estimated IRR.
 #' @rdname predict_tau
 
 summary.projoint_tau <- function(object, ...) {
   object@irr  
 }
 
-#' @param x An object of class `projoint_tau` derived from `predict_tau`
+#' @param x An object of class \code{\link{projoint_tau}} derived from \code{\link{predict_tau}}
 #' @param ... Optional arguments; currently none accepted
 #' @export
 #' @rdname predict_tau

R/projoint.R

@@ -9,24 +9,24 @@
 #' @importFrom MASS mvrnorm
 #' @importFrom methods is
 #' @importFrom methods new
-#' @param .data A `projoint_data` object
-#' @param .qoi A `projoint_qoi` object. If NULL, defaults to producing all MMs and all AMCEs.
+#' @param .data A \code{\link{projoint_data}} object
+#' @param .qoi A \code{\link{projoint_qoi}} object. If \code{NULL}, defaults to producing all MMs and all AMCEs.
 #' @param .by_var A dichotomous variable (character) used for subgroup analysis
-#' @param .structure Either "profile_level" (default) or "choice_level" 
-#' @param .estimand Either "mm" for marginal mean or "amce" for average marginal component effect
-#' @param .se_method c("analytic", "simulation", "bootstrap") description
-#' @param .irr NULL (default) if IRR is to be calculated using the repeated task. Otherwise, a numerical value
-#' @param .remove_ties Logical: should ties be removed before estimation? Defaults to TRUE.
-#' @param .ignore_position TRUE (default) if you ignore the location of profile (left or right. Relevant only if analyzed at the choice level
-#' @param .n_sims The number of simulations. Relevant only if .se_method == "simulation" 
-#' @param .n_boot The number of bootstrapped samples. Relevant only if .se_method == "bootstrap"
-#' @param .weights_1 the weight to estimate IRR (see `lm_robust()`): NULL (default)
-#' @param .clusters_1 the clusters to estimate IRR (see `lm_robust()`): NULL (default)
-#' @param .se_type_1 the standard error type to estimate IRR (see `lm_robust()`): "classical" (default)
-#' @param .weights_2 the weight to estimate MM or AMCE (see `lm_robust()`): NULL (default)
-#' @param .clusters_2 the clusters to estimate MM or AMCE (see `lm_robust()`): NULL (default)
-#' @param .se_type_2 the standard error type to estimate MM or AMCE (see `lm_robust()`): "classical" (default)
-#' @return A `projoint_results` object
+#' @param .structure Either \code{"profile_level"} (default) or \code{"choice_level"} 
+#' @param .estimand Either \code{"mm"} for marginal mean or \code{"amce"} for average marginal component effect
+#' @param .se_method By default, \code{c("analytic", "simulation", "bootstrap")} description
+#' @param .irr \code{NULL} (default) if IRR is to be calculated using the repeated task. Otherwise, a numerical value
+#' @param .remove_ties Logical: should ties be removed before estimation? Defaults to \code{TRUE}.
+#' @param .ignore_position TRUE (default) if you ignore the location of profile (left or right). Relevant only if analyzed at the choice level
+#' @param .n_sims The number of simulations. Relevant only if \code{.se_method == "simulation"} 
+#' @param .n_boot The number of bootstrapped samples. Relevant only if \code{.se_method == "bootstrap"}
+#' @param .weights_1 the weight to estimate IRR (see \code{\link[estimatr]{lm_robust}}): \code{NULL} (default)
+#' @param .clusters_1 the clusters to estimate IRR (see \code{\link[estimatr]{lm_robust}}): \code{NULL} (default)
+#' @param .se_type_1 the standard error type to estimate IRR (see \code{\link[estimatr]{lm_robust}}): \code{"classical"} (default)
+#' @param .weights_2 the weight to estimate MM or AMCE (see \code{\link[estimatr]{lm_robust}}): \code{NULL} (default)
+#' @param .clusters_2 the clusters to estimate MM or AMCE (see \code{\link[estimatr]{lm_robust}}): \code{NULL} (default)
+#' @param .se_type_2 the standard error type to estimate MM or AMCE (see \code{\link[estimatr]{lm_robust}}): \code{"classical"} (default)
+#' @return A \code{\link{projoint_results}} object
 #' @export
 #' @examples
 #' 
@@ -113,7 +113,7 @@ projoint <- function(
 }
 
 
-#' @param x A `projoint_results` object
+#' @param x A \code{\link{projoint_results}} object
 #' @param ... Optional arguments; currently none accepted
 #' @export
 #' @rdname projoint
@@ -133,7 +133,7 @@ print.projoint_results <- function(x, ...) {
 }
 
 
-#' @param object A projoint_results object
+#' @param object A \code{\link{projoint_results}} object
 #' @param ... Optional arguments; currently none accepted
 #' @export
 #' @rdname projoint

R/projoint_data.R

@@ -1,4 +1,4 @@
-#' Class generator for `projoint_data`
+#' Class generator for \code{\link{projoint_data}}
 #' @importFrom methods is
 #' @importFrom methods new
 #' @keywords internal

R/projoint_diff.R

@@ -9,24 +9,24 @@
 #' @importFrom methods is
 #' @importFrom methods new
 #' @keywords internal
-#' @param .data A `projoint_data` object
-#' @param .qoi A `projoint_qoi` object. If NULL, defaults to producing all MMs and all AMCEs.
+#' @param .data A \code{\link{projoint_data}} object
+#' @param .qoi A \code{\link{projoint_qoi}} object. If \code{NULL}, defaults to producing all MMs and all AMCEs.
 #' @param .by_var A dichotomous variable (character) used for subgroup analysis
-#' @param .structure Either "profile_level" (default) or "choice_level" 
-#' @param .estimand Either "mm" for marginal mean or "amce" for average marginal component effect
-#' @param .se_method c("analytic", "simulation", "bootstrap") description
-#' @param .irr NULL (default) if IRR is to be calculated using the repeated task. Otherwise, a numerical value
-#' @param .remove_ties Logical: should ties be removed before estimation? Defaults to TRUE.
-#' @param .ignore_position TRUE (default) if you ignore the location of profile (left or right. Relevant only if analyzed at the choice level
-#' @param .n_sims The number of simulations. Relevant only if .se_method == "simulation" 
-#' @param .n_boot The number of bootstrapped samples. Relevant only if .se_method == "bootstrap"
-#' @param .weights_1 the weight to estimate IRR (see `lm_robust()`): NULL (default)
-#' @param .clusters_1 the clusters to estimate IRR (see `lm_robust()`): NULL (default)
-#' @param .se_type_1 the standard error type to estimate IRR (see `lm_robust()`): "classical" (default)
-#' @param .weights_2 the weight to estimate MM or AMCE (see `lm_robust()`): NULL (default)
-#' @param .clusters_2 the clusters to estimate MM or AMCE (see `lm_robust()`): NULL (default)
-#' @param .se_type_2 the standard error type to estimate MM or AMCE (see `lm_robust()`): "classical" (default)
-#' @return A `projoint_results` object
+#' @param .structure Either \code{"profile_level"} (default) or \code{"choice_level"} 
+#' @param .estimand Either \code{"mm"} for marginal mean or \code{"amce"} for average marginal component effect
+#' @param .se_method By default, \code{c("analytic", "simulation", "bootstrap")} description
+#' @param .irr \code{NULL} (default) if IRR is to be calculated using the repeated task. Otherwise, a numerical value
+#' @param .remove_ties Logical: should ties be removed before estimation? Defaults to \code{TRUE}.
+#' @param .ignore_position TRUE (default) if you ignore the location of profile (left or right). Relevant only if analyzed at the choice level
+#' @param .n_sims The number of simulations. Relevant only if \code{.se_method == "simulation"} 
+#' @param .n_boot The number of bootstrapped samples. Relevant only if \code{.se_method == "bootstrap"}
+#' @param .weights_1 the weight to estimate IRR (see \code{\link[estimatr]{lm_robust}}): \code{NULL} (default)
+#' @param .clusters_1 the clusters to estimate IRR (see \code{\link[estimatr]{lm_robust}}): \code{NULL} (default)
+#' @param .se_type_1 the standard error type to estimate IRR (see \code{\link[estimatr]{lm_robust}}): \code{"classical"} (default)
+#' @param .weights_2 the weight to estimate MM or AMCE (see \code{\link[estimatr]{lm_robust}}): \code{NULL} (default)
+#' @param .clusters_2 the clusters to estimate MM or AMCE (see \code{\link[estimatr]{lm_robust}}): \code{NULL} (default)
+#' @param .se_type_2 the standard error type to estimate MM or AMCE (see \code{\link[estimatr]{lm_robust}}): \code{"classical"} (default)
+#' @return A \code{\link{projoint_results}} object
 
 projoint_diff <- function(
     .data,