diff --git a/man/rmd/proportional_hazards_glmnet.Rmd b/man/rmd/proportional_hazards_glmnet.Rmd index 8758018c5..2d9635884 100644 --- a/man/rmd/proportional_hazards_glmnet.Rmd +++ b/man/rmd/proportional_hazards_glmnet.Rmd @@ -85,14 +85,8 @@ predict(mod, pred_data, type = "survival", time = 500) %>% Note that columns used in the `strata()` function _will_ also be estimated in the regular portion of the model (i.e., within the linear predictor). # Linear predictor values - -Since risk regression and parametric survival models are modeling different characteristics (e.g. relative hazard versus event time), their linear predictors will be going in opposite directions. - -For example, for parametric models, the linear predictor _increases with time_. For proportional hazards models the linear predictor _decreases with time_ (since hazard is increasing). As such, the linear predictors for these two quantities will have opposite signs. - -tidymodels does not treat different models differently when computing performance metrics. To standardize across model types, the default for proportional hazards models is to have _increasing values with time_. As a result, the sign of the linear predictor will be the opposite of the value produced by the `predict()` method in the \pkg{survival} package. - -This behavior can be changed by using the `increasing` argument when calling `predict()` on a \pkg{parsnip} model object. +```{r child = "template-censored-linear-predictor.Rmd"} +``` # References diff --git a/man/rmd/proportional_hazards_glmnet.md b/man/rmd/proportional_hazards_glmnet.md index e1a221b41..51309af27 100644 --- a/man/rmd/proportional_hazards_glmnet.md +++ b/man/rmd/proportional_hazards_glmnet.md @@ -101,7 +101,7 @@ Since risk regression and parametric survival models are modeling different char For example, for parametric models, the linear predictor _increases with time_. For proportional hazards models the linear predictor _decreases with time_ (since hazard is increasing). As such, the linear predictors for these two quantities will have opposite signs. -tidymodels does not treat different models differently when computing performance metrics. To standardize across model types, the default for proportional hazards models is to have _increasing values with time_. As a result, the sign of the linear predictor will be the opposite of the value produced by the `predict()` method in the \pkg{survival} package. +tidymodels does not treat different models differently when computing performance metrics. To standardize across model types, the default for proportional hazards models is to have _increasing values with time_. As a result, the sign of the linear predictor will be the opposite of the value produced by the `predict()` method in the engine package. This behavior can be changed by using the `increasing` argument when calling `predict()` on a \pkg{parsnip} model object. diff --git a/man/rmd/proportional_hazards_survival.Rmd b/man/rmd/proportional_hazards_survival.Rmd index e3027247f..91065564f 100644 --- a/man/rmd/proportional_hazards_survival.Rmd +++ b/man/rmd/proportional_hazards_survival.Rmd @@ -44,14 +44,8 @@ Note that columns used in the `strata()` function will not be estimated in the r # Linear predictor values - -Since risk regression and parametric survival models are modeling different characteristics (e.g. relative hazard versus event time), their linear predictors will be going in opposite directions. - -For example, for parametric models, the linear predictor _increases with time_. For proportional hazards models the linear predictor _decreases with time_ (since hazard is increasing). As such, the linear predictors for these two quantities will have opposite signs. - -tidymodels does not treat different models differently when computing performance metrics. To standardize across model types, the default for proportional hazards models is to have _increasing values with time_. As a result, the sign of the linear predictor will be the opposite of the value produced by the `predict()` method in the \pkg{survival} package. - -This behavior can be changed by using the `increasing` argument when calling `predict()` on a \pkg{parsnip} model object. +```{r child = "template-censored-linear-predictor.Rmd"} +``` ## References diff --git a/man/rmd/proportional_hazards_survival.md b/man/rmd/proportional_hazards_survival.md index f74ad4283..c3f81d09e 100644 --- a/man/rmd/proportional_hazards_survival.md +++ b/man/rmd/proportional_hazards_survival.md @@ -91,7 +91,7 @@ Since risk regression and parametric survival models are modeling different char For example, for parametric models, the linear predictor _increases with time_. For proportional hazards models the linear predictor _decreases with time_ (since hazard is increasing). As such, the linear predictors for these two quantities will have opposite signs. -tidymodels does not treat different models differently when computing performance metrics. To standardize across model types, the default for proportional hazards models is to have _increasing values with time_. As a result, the sign of the linear predictor will be the opposite of the value produced by the `predict()` method in the \pkg{survival} package. +tidymodels does not treat different models differently when computing performance metrics. To standardize across model types, the default for proportional hazards models is to have _increasing values with time_. As a result, the sign of the linear predictor will be the opposite of the value produced by the `predict()` method in the engine package. This behavior can be changed by using the `increasing` argument when calling `predict()` on a \pkg{parsnip} model object. diff --git a/man/rmd/template-censored-linear-predictor.Rmd b/man/rmd/template-censored-linear-predictor.Rmd new file mode 100644 index 000000000..228ef91d4 --- /dev/null +++ b/man/rmd/template-censored-linear-predictor.Rmd @@ -0,0 +1,7 @@ +Since risk regression and parametric survival models are modeling different characteristics (e.g. relative hazard versus event time), their linear predictors will be going in opposite directions. + +For example, for parametric models, the linear predictor _increases with time_. For proportional hazards models the linear predictor _decreases with time_ (since hazard is increasing). As such, the linear predictors for these two quantities will have opposite signs. + +tidymodels does not treat different models differently when computing performance metrics. To standardize across model types, the default for proportional hazards models is to have _increasing values with time_. As a result, the sign of the linear predictor will be the opposite of the value produced by the `predict()` method in the engine package. + +This behavior can be changed by using the `increasing` argument when calling `predict()` on a \pkg{parsnip} model object.