27 lines
1.0 KiB
R
27 lines
1.0 KiB
R
library(tidyverse)
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dsl_csv <-"~/dsl/111725_DSL_frame.csv"
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dsl_df <- read.csv(dsl_csv, header = TRUE)
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#https://stats.oarc.ucla.edu/wp-content/uploads/2025/02/survival_r_full.html
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library(survival)
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library(broom)
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dsl_df$ttr_weeks <- dsl_df$TTR / 168
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trial.survival <- Surv(dsl_df$ttr_weeks)
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trial.model <- coxph(trial.survival ~ n_comments_before
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+ week_index + as.factor(isAuthorWMF) * as.factor(source), data=dsl_df)
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summary(trial.model)
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trial.tab <- tidy(trial.model, exponentiate=T, conf.int=T)
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ggplot(trial.tab,
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aes(y=term, x=estimate, xmin=conf.low, xmax=conf.high)) +
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geom_pointrange() + # plots center point (x) and range (xmin, xmax)
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geom_vline(xintercept=1, color="red") + # vertical line at HR=1
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labs(x="hazard ratio", title="Hazard ratios and 95% CIs") +
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theme_classic()
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surv.at.means <- survfit(trial.model)
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plot(surv.at.means, xlab="weeks", ylab="survival probability")
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#https://hbiostat.org/stat/binarysurv
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plot(surv.at.means, xlab = "weeks", ylab = "survival probability", xlim = c(0, 26))
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