Doc updates

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: WeightIt
 Type: Package
 Title: Weighting for Covariate Balance in Observational Studies
-Version: 1.3.0.9001
+Version: 1.3.0.9002
 Authors@R: c(
     person("Noah", "Greifer", role=c("aut", "cre"), 
            email = "noah.greifer@gmail.com",

NEWS.md

@@ -11,6 +11,8 @@ WeightIt News and Updates
 
 * When `missing = "saem"`, using `vcov = "FWB"` in `glm_weightit()`, etc., now appropriately results in an error. (#71)
 
+* Typo fixes in documentation.
+
 # `WeightIt` 1.3.0
 
 * Added `anova()` methods for `glm_weightit`, `multinom_weightit`, `ordinal_weightit`, and `coxph_weightit` objects to perform Wald tests for comparing nested models. The models do not have to be symbolically nested.

R/weightit.R

@@ -23,7 +23,7 @@
 #' individual pages for each method for more information on which estimands are
 #' allowed with each method and what literature to read to interpret these
 #' estimands.
-#' @param stabilize whether or not and how to stabilize the weights. If `TRUE`, each unit's weight will be multiplied by a standardization factor, which is the inverse of the unconditional probability (or density) of each unit's observed treatment value. If a formula, a generalized linear model will be fit with the included predictors, and the inverse of the corresponding weight will be used as the standardization factor. Can only be used with continuous treatments or when `estimand = "ATE"`. Default is `FALSE` for no standardization. See also the `num.formula` argument at [weightitMSM()]
+#' @param stabilize whether or not and how to stabilize the weights. If `TRUE`, each unit's weight will be multiplied by a standardization factor, which is the the unconditional probability (or density) of each unit's observed treatment value. If a formula, a generalized linear model will be fit with the included predictors, and the inverse of the corresponding weight will be used as the standardization factor. Can only be used with continuous treatments or when `estimand = "ATE"`. Default is `FALSE` for no standardization. See also the `num.formula` argument at [weightitMSM()].
 #' @param focal when multi-category treatments are used and ATT weights are
 #' requested, which group to consider the "treated" or focal group. This group
 #' will not be weighted, and the other groups will be weighted to be more like

R/weightit.fit.R

@@ -31,7 +31,7 @@
 #' @param stabilize `logical`; whether or not to stabilize the weights.
 #' For the methods that involve estimating propensity scores, this involves
 #' multiplying each unit's weight by the proportion of units in their treatment
-#' group. Default is `FALSE`.
+#' group. Default is `FALSE`. Note this differs from its use with [weightit()].
 #' @param focal when multi-category treatments are used and ATT weights are
 #' requested, which group to consider the "treated" or focal group. This group
 #' will not be weighted, and the other groups will be weighted to be more like