Построение «лестницы» с использованием ggplot2/plotly

Дело в том, что при рисовании сюжета в baseграфика рисуется прямо на устройстве. Строка вашего кода grob= plot(r_fit$unique.death.times, pred[1,], type = "l", col = "red") создает объект NULL (в отличие от ggplot, который возвращает объект графика).

Вы можете сделать график прямо в ggplot (есть несколько способов сделать это, но я сделал простой пример ниже) и преобразовать его с помощью ggplotly:

fig_dat <- data.frame(time = r_fit$unique.death.times,
                      pred_1 = t(pred[1,]),
                      fit_1 = r_fit$survival[2,],
                      fit_2 = r_fit$survival[3,])

fig_dat_long <- fig_dat %>% pivot_longer(-time, names_to = "pred_fit", values_to = "pred_fit_values")

gg_p <- ggplot(fig_dat_long, aes(x = time, y = pred_fit_values, colour = pred_fit)) +
  geom_line()

ggplotly(gg_p)

В качестве альтернативы вы также можете построить график plotly напрямую:

fig_dat <- data.frame(time = r_fit$unique.death.times,
                      pred_1 = t(pred[1,]),
                      fit_1 <- r_fit$survival[2,],
                      fit_2 <- r_fit$survival[3,])


fig <- plot_ly(fig_dat, x = ~time, y = ~pred_1, name = 'pred1', type = 'scatter', mode = 'lines')
fig <- fig %>% add_trace(y = ~fit_1, name = 'fit 1', mode = 'lines') 
fig <- fig %>% add_trace(y = ~fit_2, name = 'fit 2', mode = 'lines')

## make dataframe of variables to plot:
fig_dat <- data.frame(time = r_fit$unique.death.times,
                      pred_1 = t(pred[1,]),
                      fit_1 = r_fit$survival[2,],
                      fit_2 = r_fit$survival[3,])

# to include the variables from 'a' we need to put them in the same dataframe for plotting
# Trouble is they are different lengths the predicted data are a little shorter
dim(fig_dat)
dim(a)
# We can join the two with inner join: https://stackoverflow.com/questions/1299871/how-to-join-merge-data-frames-inner-outer-left-right
fig_dat_join <- inner_join(fig_dat, a, by = "time")
dim(fig_dat_join)
# now they are equal dimensions and joined together but we have a slight issue with duplicate values:
sort(a$time) # we can see here that time 53 appears twice for example
a$time[duplicated(a$time)] # this tells us which values in time are duplicated
sort(death_times) # some
death_times[duplicated(death_times)] #none
# because of the duplicates some combinations are returned: see rows 9 and 10
fig_dat_join 

# I'm not familiar with the analysis so I'm not sure what the correct way in this case is to remove the duplicates in 'a' so that the dimentions of 'a' match the output of 'r-fit'
# You might need to look into that but it might not make much difference to the visualisation

# I've not used plotly a great deal so there is probably a better way of doing this but I've done my best and included the links as comments: https://plotly-r.com/overview.html
# labels: https://plotly.com/r/figure-labels/
x_labs <- list(
  title = "Time")

y_labs <- list(
  title = "y axis")

# T include extra info in hovertext: I https://stackoverflow.com/questions/49901771/how-to-set-different-text-and-hoverinfo-text

p1 <- plot_ly(data = fig_dat_join,
              x = ~time,
              # text = ~n,
              # textposition = "auto",
              # hoverinfo = "text",
              hovertext = paste("Time :", fig_dat_join$time,
                                "<br> Sex :", fig_dat_join$sex,
                                "<br> Inst :", fig_dat_join$inst,
                                "<br> ID :", fig_dat_join$ID,
                                "<br> Age :", fig_dat_join$age
                                )) %>% 
  add_trace(y = ~pred_1,
            type = 'scatter',
            name = 'Predictor 1',
            mode = 'lines') %>% 
  add_trace( y = ~fit_1,
            type = 'scatter',
            name = 'Fit 1',
            mode = 'lines') %>% 
  add_trace( y = ~fit_2,
             type = 'scatter',
             name = 'Fit 2',
             mode = 'lines') %>% 
  layout(xaxis = x_labs, yaxis = y_labs)

p1

Я сопоставлял фрейм данных a с unique.death.times, используя left_join() выше. Если вам это не нужно, мы могли бы просто переместить код hovertext в каждый add_trace?

fig_dat <- data.frame(time = r_fit$unique.death.times,
                      pred_1 = t(pred[1,]),
                      fit_1 = r_fit$survival[2,],
                      fit_2 = r_fit$survival[3,])


p2 <- plot_ly(data = fig_dat,
              x = ~time,
              # text = ~n,
              # textposition = "auto",
              hoverinfo = "text"
) %>% 
  add_trace(y = ~pred_1,
            type = 'scatter',
            name = 'Predictor 1',
            mode = 'lines',
            hovertext = paste("Time :", fig_dat$time,
                              "<br> y axis :", fig_dat$pred_1,
                              "<br> Sex :", a$sex[1],
                              "<br> Inst :", a$inst[1],
                              "<br> ID :", a$ID[1],
                              "<br> Age :", a$age[1]
            )) %>% 
  add_trace( y = ~fit_1,
             type = 'scatter',
             name = 'Fit 1',
             mode = 'lines',
             hovertext = paste("Time :", fig_dat$time,
                               "<br> y axis :", fig_dat$fit_1,
                               "<br> Sex :", a$sex[2],
                               "<br> Inst :", a$inst[2],
                               "<br> ID :", a$ID[2],
                               "<br> Age :", a$age[2]
             )) %>% 
  add_trace( y = ~fit_2,
             type = 'scatter',
             name = 'Fit 2',
             mode = 'lines',
             hovertext = paste("Time :", fig_dat$time,
                               "<br> y axis :", fig_dat$fit_2,
                               "<br> Sex :", a$sex[3],
                               "<br> Inst :", a$inst[3],
                               "<br> ID :", a$ID[3],
                               "<br> Age :", a$age[3]
             )) %>% 
  layout(xaxis = x_labs, yaxis = y_labs)

p2