Predictions and confidence intervals for logistic regression

Usage

lr_predict(object, newdata, conf_level = 0.95)

Arguments

object: A logistic regression model
newdata: Data frame containing cases to be predicted
conf_level: Confidence level for the intervals

Value

A tibble

Examples

mod <- lr_model(response ~ exposure, lr_data)
prd <- lr_predict(mod, lr_data)
prd
#> # A tibble: 300 × 11
#>       id  dose exposure quartile response sex    fit_link se_link fit_resp
#>    <int> <dbl>    <dbl> <fct>       <dbl> <fct>     <dbl>   <dbl>    <dbl>
#>  1     1   100    148.  Q3              1 Male      1.80    0.248    0.858
#>  2     2   100     79.7 Q1              1 Male      1.04    0.157    0.738
#>  3     3   200    212.  Q3              1 Male      2.50    0.362    0.924
#>  4     4   200    236.  Q3              0 Female    2.77    0.407    0.941
#>  5     5     0      0   Placebo         1 Female    0.151   0.177    0.538
#>  6     6   200     71.0 Q1              1 Male      0.940   0.151    0.719
#>  7     7   100    173.  Q3              1 Male      2.08    0.292    0.889
#>  8     8   100    123.  Q2              0 Female    1.52    0.209    0.821
#>  9     9     0      0   Placebo         0 Male      0.151   0.177    0.538
#> 10    10   200    165.  Q3              1 Male      1.99    0.277    0.879
#> # ℹ 290 more rows
#> # ℹ 2 more variables: ci_lower <dbl>, ci_upper <dbl>