get_predict | R Documentation |
Get predicted values from a model object (internal function)
get_predict(model, newdata, vcov, conf_level, type, ...) ## Default S3 method: get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'polr' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "probs", ... ) ## S3 method for class 'glmmPQL' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'afex_aov' get_predict(model, newdata = NULL, ...) ## S3 method for class 'glimML' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'betareg' get_predict(model, newdata, ...) ## S3 method for class 'bife' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'biglm' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'multinom' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "probs", ... ) ## S3 method for class 'brmultinom' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "probs", ... ) ## S3 method for class 'brmsfit' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'crch' get_predict( model, newdata = NULL, vcov = FALSE, conf_level = 0.95, type = "location", ... ) ## S3 method for class 'fixest' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'gamlss' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'glmmTMB' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'merMod' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'lmerModLmerTest' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'lmerMod' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'mblogit' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'mhurdle' get_predict( model, newdata = insight::get_data(model), vcov = NULL, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'mlogit' get_predict(model, newdata, ...) ## S3 method for class 'clm' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'rq' get_predict( model, newdata = insight::get_data(model), vcov = NULL, conf_level = 0.95, type = NULL, ... ) ## S3 method for class 'rlmerMod' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'stanreg' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "response", ... ) ## S3 method for class 'coxph' get_predict( model, newdata = insight::get_data(model), vcov = FALSE, conf_level = 0.95, type = "lp", ... ) ## S3 method for class 'tobit1' get_predict( model, newdata = insight::get_data(model), vcov = NULL, conf_level = 0.95, type = "response", ... )
model |
Model object |
newdata |
|
vcov |
Type of uncertainty estimates to report (e.g., for robust standard errors). Acceptable values:
|
conf_level |
numeric value between 0 and 1. Confidence level to use to build a confidence interval. |
type |
string indicates the type (scale) of the predictions used to
compute marginal effects or contrasts. This can differ based on the model
type, but will typically be a string such as: "response", "link", "probs",
or "zero". When an unsupported string is entered, the model-specific list of
acceptable values is returned in an error message. When |
... |
Additional arguments are passed to the |
A data.frame of predicted values with a number of rows equal to the
number of rows in newdata
and columns "rowid" and "predicted". A "group"
column is added for multivariate models or models with categorical outcomes.
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