As with the ggbetweenstats(), this function also has a grouped_ variant that makes repeating the same analysis across a single grouping variable quicker. We will see an example with only repeated measurements-set.seed(123) grouped_ggwithinstats( data = dplyr::filter(bugs_long, region %in% c...
# using `ggstatsplot` to get call with statistical results stats_results <- ggstatsplot::ggbetweenstats( data = ChickWeight, x = Time, y = weight, return = "subtitle", messages = FALSE ) # using `yarrr` to create plot yarrr::pirateplot( formula = weight ~ Time, data = ChickWeight...
L. Raw Accelerometer Data Analysis with GGIR R-package: Does Accelerometer Brand Matter? Med. Sci. Sports Exerc. 48, 1935-1941 (2016).Rowlands, A. V., Yates, T., Davies, M., Khunti, K. & Edwardson, C. L. Raw Accelerometer Data Analysis with GGIR R-package: Does...
library(ggrepel)ggplot(mtcars)+geom_point(aes(wt,mpg),color="blue")+geom_text_repel(aes(wt,mpg,label=rownames(mtcars)))+theme_classic(base_size=16) 在用seurat分析单细胞数据时也常出现标签覆盖问题, 可以通过设置repel = TRUE来解决。 代码语言:javascript 代码运行次数:0 运行 AI代码解释 DimPlot(...
basic_coverage<-ggcoverage(data=track_df,plot.type="facet",mark.region=mark_region,range.position="out")basic_coverage Custom Y-axis style Change the Y-axis scale label in/out of plot region withrange.position: basic_coverage<-ggcoverage(data=track_df,plot.type="facet",mark.region=mark_re...
.data$undefined & .data$type=="gene"), fill="white", color="black")+ geom_node_text(aes(label=converted_name, filter=.data$type == "gene"), size=2.5, color="black",family="serif")+ with_outer_glow(geom_node_text(aes(label=converted_name, filter=.data$enrich_attribute), size=...
data = dat2 ) 绘图( 。_ 。) ✎ _ ggcoefstats( x = mod_coxph, title = "Proportional Hazards Regression Model\nwith Frailty penalty function" ) Note!Aalen's additive model和Cox model较为相似,满足等比例风险假设,即(Proportional hazard assumption, PH assumption)时,两种model均可选择。
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an arbitrary function defining a transformation of the survival curve. Often used transformations can be specified with a character argument: "event" plots cumulative events (f(y) = 1-y), "cumhaz" plots the cumulative hazard function (f(y) = -log(y)), and "pct" for survival probability...
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