From 4a3eeeca063df51c74cd21dedf03b2e1cf3dda3e Mon Sep 17 00:00:00 2001 From: jmgirard Date: Thu, 25 Oct 2018 22:25:59 -0400 Subject: [PATCH] Fix spelling mistakes --- R/instrument_oop.R | 2 +- R/tidying_functions.R | 2 +- docs/articles/intermediate-ssm-analysis.html | 2 +- docs/articles/introduction-to-ssm-analysis.html | 2 +- docs/reference/instrument.html | 4 ++-- docs/reference/standardize.html | 2 +- man/instrument.Rd | 2 +- man/standardize.Rd | 2 +- vignettes/intermediate-ssm-analysis.Rmd | 2 +- vignettes/introduction-to-ssm-analysis.Rmd | 2 +- 10 files changed, 11 insertions(+), 11 deletions(-) diff --git a/R/instrument_oop.R b/R/instrument_oop.R index d1b13742..721def5d 100644 --- a/R/instrument_oop.R +++ b/R/instrument_oop.R @@ -244,7 +244,7 @@ instruments <- function() { #' Load a specific instrument object #' -#' The circumplex pacakge includes information about numerous circumplex +#' The circumplex package includes information about numerous circumplex #' instruments including instructions for scoring and standardizing items to be #' used in conjunction with the \code{score} and \code{standardize} functions. #' This function loads the information for a specific instrument into memory. diff --git a/R/tidying_functions.R b/R/tidying_functions.R index c6e8c8d6..82d123b1 100644 --- a/R/tidying_functions.R +++ b/R/tidying_functions.R @@ -120,7 +120,7 @@ score <- function(.data, items, instrument, na.rm = TRUE, prefix = "", suffix = #' to use in standardizing the scale scores (default = 1). See \code{?norms} #' to see the normative samples available for an instrument. #' @param prefix Optional. A string to include at the beginning of the newly -#' calcualted scale variables' names, before the scale name and \code{suffix} +#' calculated scale variables' names, before the scale name and \code{suffix} #' (default = ""). #' @param suffix Optional. A string to include at the end of the newly #' calculated scale variables' names, after the scale name and \code{prefix} diff --git a/docs/articles/intermediate-ssm-analysis.html b/docs/articles/intermediate-ssm-analysis.html index d61ae0bf..6e00df0f 100644 --- a/docs/articles/intermediate-ssm-analysis.html +++ b/docs/articles/intermediate-ssm-analysis.html @@ -1110,7 +1110,7 @@

Wrap-up

-

In this vignette, we learned how to generalize the SSM analyses to multiple groups and measures, how to conduct contrast analyses, how to make basic customizations to tables and figures, and how to export tables and figures to external files. In the next vignette, “Advanced Circumplex Vizualiation,” we will learn more advanced customization options for the SSM figures and other circumplex visualizations. (Note that the next vignette is still in progress.)

+

In this vignette, we learned how to generalize the SSM analyses to multiple groups and measures, how to conduct contrast analyses, how to make basic customizations to tables and figures, and how to export tables and figures to external files. In the next vignette, “Advanced Circumplex Visualization,” we will learn more advanced customization options for the SSM figures and other circumplex visualizations. (Note that the next vignette is still in progress.)

diff --git a/docs/articles/introduction-to-ssm-analysis.html b/docs/articles/introduction-to-ssm-analysis.html index 8f547cbc..b99c3f94 100644 --- a/docs/articles/introduction-to-ssm-analysis.html +++ b/docs/articles/introduction-to-ssm-analysis.html @@ -224,7 +224,7 @@

#> Amplitude 0.131 0.099 0.166 #> Displacement 353.525 338.869 9.610 #> Model Fit 0.710

-

That was pretty easy! We can now write up these results. However, the circumplex package has some features that can make what we just did even easier. First, because the first three arguments of the ssm_analyze() function are always the same, we can omit their names. Second, because we organized the jz2017s data frame to have the circumplex scale variables adjacent and in order from PA to NO, we can simplify their specification by using the PA:NO shortcut. Finally, because the use of octant scales is so common, the circumplex package comes with a convenience function for outputing their angular displacements: octants(). Note how, even when using these shortcuts, the results are the same except for minor stochastic differences in the confidence intervals due to the randomness inherent to bootstrapping. (To get the exact same results, we could use the set.seed() function to control the random number generator in R.)

+

That was pretty easy! We can now write up these results. However, the circumplex package has some features that can make what we just did even easier. First, because the first three arguments of the ssm_analyze() function are always the same, we can omit their names. Second, because we organized the jz2017s data frame to have the circumplex scale variables adjacent and in order from PA to NO, we can simplify their specification by using the PA:NO shortcut. Finally, because the use of octant scales is so common, the circumplex package comes with a convenience function for outputting their angular displacements: octants(). Note how, even when using these shortcuts, the results are the same except for minor stochastic differences in the confidence intervals due to the randomness inherent to bootstrapping. (To get the exact same results, we could use the set.seed() function to control the random number generator in R.)

results2 <- ssm_analyze(jz2017s, PA_z:NO_z, octants())
 summary(results2)
 #> Call:
diff --git a/docs/reference/instrument.html b/docs/reference/instrument.html
index 020d222e..7ec2b9a7 100644
--- a/docs/reference/instrument.html
+++ b/docs/reference/instrument.html
@@ -38,7 +38,7 @@
 
 
 
-
     
-    
The circumplex pacakge includes information about numerous circumplex
+    
The circumplex package includes information about numerous circumplex
 instruments including instructions for scoring and standardizing items to be
 used in conjunction with the score and standardize functions.
 This function loads the information for a specific instrument into memory.
diff --git a/docs/reference/standardize.html b/docs/reference/standardize.html
index 857e5f34..e5433f1c 100644
--- a/docs/reference/standardize.html
+++ b/docs/reference/standardize.html
@@ -184,7 +184,7 @@ 
Arg
     
       prefix
       
Optional. A string to include at the beginning of the newly
-calcualted scale variables' names, before the scale name and suffix
+calculated scale variables' names, before the scale name and suffix
 (default = "").

     
     
diff --git a/man/instrument.Rd b/man/instrument.Rd
index 3e16683b..4ca34490 100644
--- a/man/instrument.Rd
+++ b/man/instrument.Rd
@@ -18,7 +18,7 @@ will be created in the global environment with the default name as above.
 Or, if a name is assigned (LHS), the object will have that name instead.
 }
 \description{
-The circumplex pacakge includes information about numerous circumplex
+The circumplex package includes information about numerous circumplex
 instruments including instructions for scoring and standardizing items to be
 used in conjunction with the \code{score} and \code{standardize} functions.
 This function loads the information for a specific instrument into memory.
diff --git a/man/standardize.Rd b/man/standardize.Rd
index 43324f79..d241f33d 100644
--- a/man/standardize.Rd
+++ b/man/standardize.Rd
@@ -25,7 +25,7 @@ to use in standardizing the scale scores (default = 1). See \code{?norms}
 to see the normative samples available for an instrument.}
 
 \item{prefix}{Optional. A string to include at the beginning of the newly
-calcualted scale variables' names, before the scale name and \code{suffix}
+calculated scale variables' names, before the scale name and \code{suffix}
 (default = "").}
 
 \item{suffix}{Optional. A string to include at the end of the newly
diff --git a/vignettes/intermediate-ssm-analysis.Rmd b/vignettes/intermediate-ssm-analysis.Rmd
index 5db708f0..01cdf392 100644
--- a/vignettes/intermediate-ssm-analysis.Rmd
+++ b/vignettes/intermediate-ssm-analysis.Rmd
@@ -261,7 +261,7 @@ ggsave(filename = "bordpd_gender.png", plot = p, width = 7.5, height = 4,
 ```
 
 ## Wrap-up
-In this vignette, we learned how to generalize the SSM analyses to multiple groups and measures, how to conduct contrast analyses, how to make basic customizations to tables and figures, and how to export tables and figures to external files. In the next vignette, "Advanced Circumplex Vizualiation," we will learn more advanced customization options for the SSM figures and other circumplex visualizations. (Note that the next vignette is still in progress.)
+In this vignette, we learned how to generalize the SSM analyses to multiple groups and measures, how to conduct contrast analyses, how to make basic customizations to tables and figures, and how to export tables and figures to external files. In the next vignette, "Advanced Circumplex Visualization," we will learn more advanced customization options for the SSM figures and other circumplex visualizations. (Note that the next vignette is still in progress.)
 
 ## References
 * Gurtman, M. B. (1992). Construct validity of interpersonal personality measures: The interpersonal circumplex as a nomological net. _Journal of Personality and Social Psychology, 63_(1), 105–118.
diff --git a/vignettes/introduction-to-ssm-analysis.Rmd b/vignettes/introduction-to-ssm-analysis.Rmd
index 53f708cf..a953424f 100644
--- a/vignettes/introduction-to-ssm-analysis.Rmd
+++ b/vignettes/introduction-to-ssm-analysis.Rmd
@@ -381,7 +381,7 @@ The output of the function has been saved in the `results` object, which we can
 summary(results)
 ```
 
-That was pretty easy! We can now write up these results. However, the `circumplex` package has some features that can make what we just did even easier. First, because the first three arguments of the `ssm_analyze()` function are always the same, we can omit their names. Second, because we organized the `jz2017s` data frame to have the circumplex scale variables adjacent and in order from PA to NO, we can simplify their specification by using the `PA:NO` shortcut. Finally, because the use of octant scales is so common, the `circumplex` package comes with a convenience function for outputing their angular displacements: `octants()`. Note how, even when using these shortcuts, the results are the same except for minor stochastic differences in the confidence intervals due to the randomness inherent to bootstrapping. (To get the exact same results, we could use the `set.seed()` function to control the random number generator in R.)
+That was pretty easy! We can now write up these results. However, the `circumplex` package has some features that can make what we just did even easier. First, because the first three arguments of the `ssm_analyze()` function are always the same, we can omit their names. Second, because we organized the `jz2017s` data frame to have the circumplex scale variables adjacent and in order from PA to NO, we can simplify their specification by using the `PA:NO` shortcut. Finally, because the use of octant scales is so common, the `circumplex` package comes with a convenience function for outputting their angular displacements: `octants()`. Note how, even when using these shortcuts, the results are the same except for minor stochastic differences in the confidence intervals due to the randomness inherent to bootstrapping. (To get the exact same results, we could use the `set.seed()` function to control the random number generator in R.)
 
 ```{r summary1b}
 results2 <- ssm_analyze(jz2017s, PA_z:NO_z, octants())