Readme file is revised.

README.Rmd

@@ -23,33 +23,33 @@ _Please feel free to_ [create an issue](https://github.com/SeewooLi/IRTest/issue
 [![CRAN status](https://www.r-pkg.org/badges/version/IRTest)](https://CRAN.R-project.org/package=IRTest)
 <!-- badges: end -->
 
-**IRTest** can be a useful tool for IRT (item response theory) parameter estimation, especially when the violation of normality assumption on latent distribution is suspected. \
+**IRTest** is a useful tool for IRT (item response theory) parameter estimation, especially when the violation of normality assumption on latent distribution is suspected. \
 **IRTest** deals with uni-dimensional latent variable. \
-In **IRTest**, along with the conventional approach that assumes normality on latent distribution, several methods can be applied for estimation of latent distribution: \
+In **IRTest**, including the conventional assumption of normality on latent distribution, several methods can be applied for estimation of latent distribution: \
     + empirical histogram method, \
     + two-component Gaussian mixture distribution, \
     + Davidian curve, \
     + kernel density estimation.
 
 ## Installation
 
-You can install **IRTest** on R-console with:
+**IRTest** can be installed on R-console with:
 
 ``` r
 install.packages("IRTest")
 ```
 
 ## Functions
 
-Followings are functions of **IRTest** available for users.
+Followings are functions of **IRTest**.
 
-  + `IRTest_Dich` is the estimation function when all items are dichotomously scored.
+  + `IRTest_Dich` is the estimation function when all items are *dichotomously* scored.
 
-  + `IRTest_Poly` is the estimation function when all items are polytomously scored.
+  + `IRTest_Poly` is the estimation function when all items are *polytomously* scored.
 
-  + `IRTest_Mix` is the estimation function for a mixed-format test, a combination of dichotomous item(s) and polytomous item(s).
+  + `IRTest_Mix` is the estimation function for *a mixed-format test*, a test comprising both dichotomous item(s) and polytomous item(s).
 
-  + `DataGeneration` generates several objects that are useful for computer simulation studies. Among these are starting values for an algorithm and artificial item-response data that can be passed to `IRTest_Dich`, `IRTest_Poly`, or `IRTest_Mix`
+  + `DataGeneration` generates several objects that can be useful for computer simulation studies. Among these are starting values for the estimation algorithm and artificial item-response data that can be passed into `IRTest_Dich`, `IRTest_Poly`, or `IRTest_Mix`.
 
   + `plot_LD` draws a plot of the estimated latent distribution.
 
@@ -59,13 +59,15 @@ Followings are functions of **IRTest** available for users.
 
 ## Example
 
-A simulation study for a Rasch model can be done in following manners:
+A simple simulation study for a Rasch model can be done in following manners:
 
 ```{r library}
 library(IRTest)
 ```
 
-* An artificial data of 1000 examinees and 20 items.
+* Data generation
+
+An artificial data of 1000 examinees and 20 items.
 
 ```{r generation}
 Alldata <- DataGeneration(seed = 123456789,
@@ -120,7 +122,7 @@ plot(theta, Mod1$theta, xlab = "true", ylab = "estimated", main = "ability param
 abline(a=0,b=1)
 ```
 
-* Result of latent distribution estimation
+* The result of latent distribution estimation
 
 ```{r plotLD, fig.align='center', fig.height=4, fig.width=8}
 plot_LD(Mod1)+
@@ -134,7 +136,7 @@ plot_LD(Mod1)+
   theme_bw()
 ```
 
-* Posterior distribution for examinees
+* Posterior distributions for the examinees
 
 Each examinee's posterior distribution is identified in the E-step of the estimation algorithm (i.e., EM algorithm).
 Posterior distributions can be found in `Mod1$Pk`.

README.md

@@ -14,43 +14,43 @@ potential improvements.*
 status](https://www.r-pkg.org/badges/version/IRTest)](https://CRAN.R-project.org/package=IRTest)
 <!-- badges: end -->
 
-**IRTest** can be a useful tool for IRT (item response theory) parameter
+**IRTest** is a useful tool for IRT (item response theory) parameter
 estimation, especially when the violation of normality assumption on
 latent distribution is suspected.  
 **IRTest** deals with uni-dimensional latent variable.  
-In **IRTest**, along with the conventional approach that assumes
-normality on latent distribution, several methods can be applied for
-estimation of latent distribution:  
+In **IRTest**, including the conventional assumption of normality on
+latent distribution, several methods can be applied for estimation of
+latent distribution:  
 + empirical histogram method,  
 + two-component Gaussian mixture distribution,  
 + Davidian curve,  
 + kernel density estimation.
 
 ## Installation
 
-You can install **IRTest** on R-console with:
+**IRTest** can be installed on R-console with:
 
 ``` r
 install.packages("IRTest")
 ```
 
 ## Functions
 
-Followings are functions of **IRTest** available for users.
+Followings are functions of **IRTest**.
 
 - `IRTest_Dich` is the estimation function when all items are
-  dichotomously scored.
+  *dichotomously* scored.
 
 - `IRTest_Poly` is the estimation function when all items are
-  polytomously scored.
+  *polytomously* scored.
 
-- `IRTest_Mix` is the estimation function for a mixed-format test, a
-  combination of dichotomous item(s) and polytomous item(s).
+- `IRTest_Mix` is the estimation function for *a mixed-format test*, a
+  test comprising both dichotomous item(s) and polytomous item(s).
 
-- `DataGeneration` generates several objects that are useful for
-  computer simulation studies. Among these are starting values for an
-  algorithm and artificial item-response data that can be passed to
-  `IRTest_Dich`, `IRTest_Poly`, or `IRTest_Mix`
+- `DataGeneration` generates several objects that can be useful for
+  computer simulation studies. Among these are starting values for the
+  estimation algorithm and artificial item-response data that can be
+  passed into `IRTest_Dich`, `IRTest_Poly`, or `IRTest_Mix`.
 
 - `plot_LD` draws a plot of the estimated latent distribution.
 
@@ -62,7 +62,8 @@ Followings are functions of **IRTest** available for users.
 
 ## Example
 
-A simulation study for a Rasch model can be done in following manners:
+A simple simulation study for a Rasch model can be done in following
+manners:
 
 ``` r
 library(IRTest)
@@ -71,7 +72,9 @@ library(IRTest)
 #> Li, S. (2022). IRTest: Parameter estimation of item response theory with estimation of latent distribution (Version 0.1.0). R package. URL: https://CRAN.R-project.org/package=IRTest
 ```
 
-- An artificial data of 1000 examinees and 20 items.
+- Data generation
+
+An artificial data of 1000 examinees and 20 items.
 
 ``` r
 Alldata <- DataGeneration(seed = 123456789,
@@ -195,7 +198,7 @@ abline(a=0,b=1)
 
 <img src="man/figures/README-results-1.png" width="100%" style="display: block; margin: auto;" />
 
-- Result of latent distribution estimation
+- The result of latent distribution estimation
 
 ``` r
 plot_LD(Mod1)+
@@ -218,7 +221,7 @@ plot_LD(Mod1)+
 
 <img src="man/figures/README-plotLD-1.png" width="100%" style="display: block; margin: auto;" />
 
-- Posterior distribution for examinees
+- Posterior distributions for the examinees
 
 Each examinee’s posterior distribution is identified in the E-step of
 the estimation algorithm (i.e., EM algorithm). Posterior distributions