Description Usage Arguments Value Examples
This function uses a fitted cox regression model to predict failure probabilities with the survest function from the rms package. Failure is defined as 1 - survival probability, and indicates the probability that an event does happen before a certain time. In this case, the failure probability at time t for a question is the probability that a question receives an answer before time t.
1 | predict_failure(model, newdata = NULL, times = c(0.5, 3, 10, 24, 100, 1000))
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model |
The cox regression model to use for predictions (output from the fit_model function). This function only works with cph fits, not coxph fits. |
newdata |
Optional, new data from which to get predictions for. If this is omitted, this function will output predictions for all subjects linear predictor and strata values at the default/user-specified times. |
times |
Vector of times at which to predict on. If omitted, this function will return predictions at 0.5, 3, 10, 24, 100, 1000 hours. |
Returns a data frame of predicted failure probabilities. The columns are the times predicted on, the rows correspond to each question in the data.
1 2 3 4 5 6 7 8 9 10 11 | # importing data
dir <- file.path(getwd(),"data")
out <- read.csv(file.path(dir, "answers_data.csv")) # data set without any variables set up
# fitting model
model <- fit_model(out)
# setting up variables in the prediction data
data_for_predicting <- variable_setup(newdata, forpredicting = TRUE)
predictions <- predict_failure(model, newdata = data_for_predicting)
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