add theme example in readme.md

R/svyjskm.R

@@ -286,13 +286,20 @@ svyjskm <- function(sfit,
       legend.key = element_rect(colour = NA),
       panel.border = element_blank(),
       plot.margin = unit(c(0, 1, .5, ifelse(m < 10, 1.5, 2.5)), "lines"),
-      panel.grid.major = element_blank(),
       axis.line.x = element_line(linewidth = 0.5, linetype = "solid", colour = "black"),
       axis.line.y = element_line(linewidth = 0.5, linetype = "solid", colour = "black")
     ) +
     scale_x_continuous(xlabs, breaks = times, limits = xlims) +
     scale_y_continuous(ylabs, limits = ylims, labels = scale_labels)
-
+
+  if(!is.null(theme)&&theme=='jama'){
+    p<-p+theme(
+      panel.grid.major.x = element_blank()
+    )
+  } else{
+    p <- p + theme(
+      panel.grid.major = element_blank()
+    )}
 
 
   # Removes the legend:

README.Rmd

@@ -77,6 +77,17 @@ jskm(fit2, mark = F, surv.scale = "percent", table = T, status.cmprsk = "1")
 jskm(fit2, mark = F, surv.scale = "percent", table = T, status.cmprsk = "1", showpercent = T, cut.landmark = 500)
 ```
 
+### Theme Jama
+
+```{r}
+jskm(fit, theme='jama', cumhaz = T, table=T, mark = F, ylab = "Cumulative incidence (%)", surv.scale = "percent", pval =T, pval.size = 6, pval.coord = c(300, 0.7))
+```
+
+### Theme Nejmoa
+
+```{r}
+jskm(fit, theme='nejm', nejm.infigure.ratiow = 0.6, nejm.infigure.ratioh = 0.4, nejm.infigure.ylim = c(0,0.7), cumhaz = T, table=T, mark = F, ylab = "Cumulative incidence (%)", surv.scale = "percent", pval =T, pval.size = 6, pval.coord = c(300, 0.7))
+```
 
 ### Weighted Kaplan-Meier plot - `svykm.object` in **survey** package
 
@@ -106,3 +117,14 @@ svyjskm(s3, ci = F)
 svyjskm(s3, ci = F, surv.scale = "percent", pval = T, table = T, cut.landmark = 1000, showpercent = T)
 ```
 
+### Theme jama
+
+```{r}
+svyjskm(s2, theme='jama', pval = T,  table = T, design = dpbc)
+```
+
+### Theme nejmoa
+
+```{r}
+svyjskm(s2, theme='nejm', nejm.infigure.ratiow = 0.4, nejm.infigure.ratioh = 0.4, nejm.infigure.ylim = c(0.2,1), pval = T,  table = T, design = dpbc)
+```

README.md

@@ -35,43 +35,45 @@ library(jskm)
 ### Survival probability
 
 ``` r
-#Load dataset
+# Load dataset
 library(survival)
 data(colon)
-fit <- survfit(Surv(time,status)~rx, data=colon)
+fit <- survfit(Surv(time, status) ~ rx, data = colon)
 
-#Plot the data
+# Plot the data
 jskm(fit)
 ```
 
 ![](man/figures/README-unnamed-chunk-1-1.png)<!-- -->
 
 ``` r
-jskm(fit, table = T, pval = T, label.nrisk = "No. at risk", size.label.nrisk = 8, 
-     xlabs = "Time(Day)", ylabs = "Survival", ystratalabs = c("Obs", "Lev", "Lev + 5FU"), ystrataname = "rx",
-     marks = F, timeby = 365, xlims = c(0, 3000), ylims = c(0.25, 1), showpercent = T)
+jskm(fit,
+  table = T, pval = T, label.nrisk = "No. at risk", size.label.nrisk = 8,
+  xlabs = "Time(Day)", ylabs = "Survival", ystratalabs = c("Obs", "Lev", "Lev + 5FU"), ystrataname = "rx",
+  marks = F, timeby = 365, xlims = c(0, 3000), ylims = c(0.25, 1), showpercent = T
+)
 ```
 
 ![](man/figures/README-unnamed-chunk-1-2.png)<!-- -->
 
 ### Cumulative hazard: 1- Survival probability
 
 ``` r
-jskm(fit, ci = T, cumhaz = T,  mark = F, ylab = "Cumulative incidence (%)", surv.scale = "percent", pval =T, pval.size = 6, pval.coord = c(300, 0.7))
+jskm(fit, ci = T, cumhaz = T, mark = F, ylab = "Cumulative incidence (%)", surv.scale = "percent", pval = T, pval.size = 6, pval.coord = c(300, 0.7))
 ```
 
 ![](man/figures/README-unnamed-chunk-2-1.png)<!-- -->
 
 ### Landmark analysis
 
 ``` r
-jskm(fit, mark = F,  surv.scale = "percent", pval =T, table = T, cut.landmark = 500)
+jskm(fit, mark = F, surv.scale = "percent", pval = T, table = T, cut.landmark = 500)
 ```
 
 ![](man/figures/README-unnamed-chunk-3-1.png)<!-- -->
 
 ``` r
-jskm(fit, mark = F,  surv.scale = "percent", pval =T, table = T, cut.landmark = 500, showpercent = T)
+jskm(fit, mark = F, surv.scale = "percent", pval = T, table = T, cut.landmark = 500, showpercent = T)
 ```
 
 ![](man/figures/README-unnamed-chunk-3-2.png)<!-- -->
@@ -85,7 +87,7 @@ jskm(fit, mark = F,  surv.scale = "percent", pval =T, table = T, cut.landmark =
 colon$status2 <- colon$status
 colon$status2[1:400] <- 2
 colon$status2 <- factor(colon$status2)
-fit2 <- survfit(Surv(time,status2)~rx, data=colon)
+fit2 <- survfit(Surv(time, status2) ~ rx, data = colon)
 jskm(fit2, mark = F, surv.scale = "percent", table = T, status.cmprsk = "1")
 ```
 
@@ -97,55 +99,87 @@ jskm(fit2, mark = F, surv.scale = "percent", table = T, status.cmprsk = "1", sho
 
 ![](man/figures/README-unnamed-chunk-4-2.png)<!-- -->
 
+### Theme Jama
+
+``` r
+jskm(fit, theme='jama', cumhaz = T, table=T, mark = F, ylab = "Cumulative incidence (%)", surv.scale = "percent", pval =T, pval.size = 6, pval.coord = c(300, 0.7))
+```
+
+![](man/figures/README-unnamed-chunk-5-1.png)<!-- -->
+
+### Theme Nejmoa
+
+``` r
+jskm(fit, theme='nejm', nejm.infigure.ratiow = 0.6, nejm.infigure.ratioh = 0.4, nejm.infigure.ylim = c(0,0.7), cumhaz = T, table=T, mark = F, ylab = "Cumulative incidence (%)", surv.scale = "percent", pval =T, pval.size = 6, pval.coord = c(300, 0.7))
+```
+
+![](man/figures/README-unnamed-chunk-6-1.png)<!-- -->
+
 ### Weighted Kaplan-Meier plot - `svykm.object` in **survey** package
 
 ``` r
 library(survey)
-data(pbc, package="survival")
-pbc$randomized <- with(pbc, !is.na(trt) & trt>0)
-biasmodel <- glm(randomized~age*edema,data=pbc)
+data(pbc, package = "survival")
+pbc$randomized <- with(pbc, !is.na(trt) & trt > 0)
+biasmodel <- glm(randomized ~ age * edema, data = pbc)
 pbc$randprob <- fitted(biasmodel)
 
-dpbc<-svydesign(id=~1, prob=~randprob, strata=~edema, data=subset(pbc,randomized))
+dpbc <- svydesign(id = ~1, prob = ~randprob, strata = ~edema, data = subset(pbc, randomized))
 
-s1 <-svykm(Surv(time,status>0) ~ 1, design = dpbc)
-s2 <-svykm(Surv(time,status>0) ~ sex, design = dpbc)
+s1 <- svykm(Surv(time, status > 0) ~ 1, design = dpbc)
+s2 <- svykm(Surv(time, status > 0) ~ sex, design = dpbc)
 
 svyjskm(s1)
 ```
 
-![](man/figures/README-unnamed-chunk-5-1.png)<!-- -->
+![](man/figures/README-unnamed-chunk-7-1.png)<!-- -->
 
 ``` r
-svyjskm(s2, pval = T,  table = T, design = dpbc)
+svyjskm(s2, pval = T, table = T, design = dpbc)
 ```
 
-![](man/figures/README-unnamed-chunk-5-2.png)<!-- -->
+![](man/figures/README-unnamed-chunk-7-2.png)<!-- -->
 
 ``` r
-svyjskm(s2, cumhaz = T, ylab = "Cumulative incidence (%)", surv.scale = "percent", pval = T, design = dpbc, pval.coord = c(300, 0.7), showpercent = T) 
+svyjskm(s2, cumhaz = T, ylab = "Cumulative incidence (%)", surv.scale = "percent", pval = T, design = dpbc, pval.coord = c(300, 0.7), showpercent = T)
 ```
 
-![](man/figures/README-unnamed-chunk-5-3.png)<!-- -->
+![](man/figures/README-unnamed-chunk-7-3.png)<!-- -->
 
 If you want to get **confidence interval**, you should apply `se = T`
 option to `svykm` object.
 
 ``` r
-s3 <- svykm(Surv(time,status>0) ~ sex, design=dpbc, se = T)
+s3 <- svykm(Surv(time, status > 0) ~ sex, design = dpbc, se = T)
 svyjskm(s3)
 ```
 
-![](man/figures/README-unnamed-chunk-6-1.png)<!-- -->
+![](man/figures/README-unnamed-chunk-8-1.png)<!-- -->
 
 ``` r
 svyjskm(s3, ci = F)
 ```
 
-![](man/figures/README-unnamed-chunk-6-2.png)<!-- -->
+![](man/figures/README-unnamed-chunk-8-2.png)<!-- -->
+
+``` r
+svyjskm(s3, ci = F, surv.scale = "percent", pval = T, table = T, cut.landmark = 1000, showpercent = T)
+```
+
+![](man/figures/README-unnamed-chunk-8-3.png)<!-- -->
+
+### Theme jama
+
+``` r
+svyjskm(s2, theme='jama', pval = T,  table = T, design = dpbc)
+```
+
+![](man/figures/README-unnamed-chunk-9-1.png)<!-- -->
+
+### Theme nejmoa
 
 ``` r
-svyjskm(s3, ci = F,  surv.scale = "percent", pval =T, table = T, cut.landmark = 1000, showpercent = T)
+svyjskm(s2, theme='nejm', nejm.infigure.ratiow = 0.4, nejm.infigure.ratioh = 0.4, nejm.infigure.ylim = c(0.2,1), pval = T,  table = T, design = dpbc)
 ```
 
-![](man/figures/README-unnamed-chunk-6-3.png)<!-- -->
+![](man/figures/README-unnamed-chunk-10-1.png)<!-- -->

vignettes/jskm.Rmd

@@ -70,6 +70,17 @@ jskm(fit2, mark = F, surv.scale = "percent", table = T, status.cmprsk = "1")
 jskm(fit2, mark = F, surv.scale = "percent", table = T, status.cmprsk = "1", showpercent = T, cut.landmark = 500)
 ```
 
+### Theme Jama
+
+```{r}
+jskm(fit, theme='jama', cumhaz = T, table=T, mark = F, ylab = "Cumulative incidence (%)", surv.scale = "percent", pval =T, pval.size = 6, pval.coord = c(300, 0.7))
+```
+
+### Theme Nejmoa
+
+```{r}
+jskm(fit, theme='nejm', nejm.infigure.ratiow = 0.6, nejm.infigure.ratioh = 0.4, nejm.infigure.ylim = c(0,0.7), cumhaz = T, table=T, mark = F, ylab = "Cumulative incidence (%)", surv.scale = "percent", pval =T, pval.size = 6, pval.coord = c(300, 0.7))
+```
 
 ### Weighted Kaplan-Meier plot - `svykm.object` in **survey** package
 
@@ -99,3 +110,15 @@ svyjskm(s3, ci = F, showpercent = T)
 svyjskm(s3, ci = F, surv.scale = "percent", pval = T, table = T, cut.landmark = 1000)
 ```
 
+### Theme jama
+
+```{r}
+svyjskm(s2, theme='jama', pval = T,  table = T, design = dpbc)
+```
+
+### Theme nejmoa
+
+```{r}
+svyjskm(s2, theme='nejm', nejm.infigure.ratiow = 0.4, nejm.infigure.ratioh = 0.4, nejm.infigure.ylim = c(0.2,1), pval = T,  table = T, design = dpbc)
+```
+